Electronics and communications engineering Books

Book SynopsisIntroduces advanced high-capacity data encoding and throughput improvement techniques for fully printable multi-bit Chipless RFID tags and reader systems The book proposes new approaches to chipless RFID tag encoding and tag detection that supersede their predecessors in signal processing, tag design, and reader architectures. The text is divided into two main sections: the first section introduces the fundamentals of electromagnetic (EM) imaging at mm-wave band to enhance the content capacity of Chipless RFID systems. The EM Imaging through Synthetic Aperture Radar (SAR) technique is used for data extraction. The second section presents a few smart tag detection techniques for existing chipless RFID systems. A Multiple-Input and Multiple-Output (MIMO) based tag detection technique improves the spectral efficiency and increases data bit capacity. The book concludes with a discussion of how the MIMO approach can be combined with the image based technique to introduce a Table of ContentsPreface xiAcknowledgment xvPART I EM IMAGE-BASED CHIPLESS RFID SYSTEM 11 Introduction 31.1 Barcodes as Identification Technology 41.2 RFID Systems 61.3 Barcodes Versus RFID 71.4 Chipless RFID Tag for Low-Cost Item Tagging 71.5 Chipless RFID Systems 101.6 Spatial-Based Chipless RFID System 161.7 Book Outline 17References 202 EM Imaging 252.1 EM-Imaging Fundamentals 252.2 Range Resolution 272.3 Cross-Range or Azimuth Resolution 292.4 Synthetic Aperture Radar (SAR) Necessity 312.5 EM Imaging for Content Coding 342.6 Conclusions 35References 363 Tiny Polarizers Secret of the New Technique 373.1 Introduction 373.2 Sweetness of Diffraction 393.3 Strip-Line Polarizer 433.4 Meander-Line Polarizer 453.5 Multiple Polarizers 473.6 Polarizer Fabrication 503.7 Conclusions 52References 534 Attributes of EM Polarizers 554.1 Introduction 554.2 Suggested Structures as Effective EM Polarizers 564.3 Cross-Polar Working Basis 594.4 Effect of Highly Reflective Items 644.5 Secure Identification 684.6 Bending Effect on Tag Performance 714.7 Conclusion 74References 765 System Technical Aspects 775.1 Introduction 775.2 The mm-Band of 60 GHz 775.3 Reader Antenna 815.4 Conclusions 106References 1076 SAR-Based Signal Processing 1116.1 Introduction 1116.2 SAR Modes of Operation 1126.3 SAR Block Diagram 1136.4 SAR-Based Signal Processing 1136.5 Tag Imaging Results 1166.6 System Downsides 1256.7 Conclusions 128References 1297 Fast Imaging Through MIMO-SAR 1317.1 Introduction 1317.2 Conventional Phased Array Antenna 1327.3 MIMO-SAR Systems 1337.4 Optimization 1437.5 MIMO-SAR Results 1557.6 Conclusion 158References 159PART II ADVANCED TAG DETECTION TECHNIQUES FOR CHIPLESS RFID SYSTEMS 1618 Introduction 1638.1 RFID Systems 1638.2 Review of Chipless RFID Tag Detection Techniques 1678.3 Maximum Likelihood Detection Techniques 1688.4 Conclusions 170References 1709 Chipless RFID Tag Design 1779.1 Introduction 1779.2 SISO Tag Design 1779.3 MIMO Tag Design 1799.4 Conclusions 188References 18810 ML Detection Techniques for SISO Chipless RFID Tags 18910.1 Introduction 18910.2 System Models–Time Domain 19010.3 System Models–Frequency Domain 20010.4 Simulations 20510.5 Experimental Setup 20710.6 Results 20810.7 Conclusion 230References 23011 Computationally Feasible Tag Detection Techniques 23311.1 Introduction 23311.2 Bit-By-Bit Detection Method 23411.3 Trellis-Tree-Based Viterbi Decoding 23711.4 Simulation Setup 24211.5 Results 24411.6 Conclusions 246References 24612 Signal Processing for MIMO-Based Chipless RFID Systems 24712.1 Introduction 24712.2 MIMO Decomposing Techniques 24912.3 Tag Detection in MIMO 25112.4 Experimental Setup 25312.5 Simulations 25412.6 Results 25812.7 Conclusion 268Reference 26813 Conclusion for Part II 26913.1 Summary of The Proposed Techniques in Part II 26913.2 Limitations of The Proposed System 27113.3 Potential Applications 27213.4 Future Work and Open Issues 273Reference 274Index 275

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Book SynopsisApplies lean manufacturing principles across the cloud service delivery chain to enable application and infrastructure service providers to sustainably achieve the shortest lead time, best quality, and value Applies lean thinking across the cloud service delivery chain to recognize and minimize wasteLeverages lessons learned from electric power industry operations to operations of cloud infrastructureApplies insights from just-in-time inventory management to operation of cloud based applicationsExplains how traditional, Information Technology Infrastructure Library (ITIL) and Enhanced Telecom Operation Map (eTOM) capacity management evolves to lean computing for the cloud Table of ContentsIntroduction xi Acknowledgments xv Abbreviations xvii 1. Basics 1 1.1 Cloud Computing Fundamentals 1 1.2 Roles in Cloud Computing 6 1.3 Applications 9 1.3.1 Application Service Quality 11 1.4 Demand, Supply, Capacity, and Fungibility 13 1.5 Demand Variability 16 1.6 Chapter Review 18 2. Rethinking Capacity Management 19 2.1 Capacity Management 19 2.2 Demand Management 21 2.3 Performance Management 21 2.4 Canonical Capacity Management 23 2.4.1 Traditional Capacity Management 24 2.4.2 ITIL Capacity Management 27 2.4.3 eTOM Capacity Management 28 2.4.4 Discussion 30 2.5 Three Cloud Capacity Management Problems 30 2.5.1 Physical Resource Capacity Management 31 2.5.2 Virtual Resource Capacity Management 32 2.5.3 Application Capacity Management 33 2.6 Cloud Capacity Management as a Value Chain 36 2.7 Chapter Review 39 3. Lean Thinking on Cloud Capacity Management 41 3.1 Lean Thinking Overview 41 3.2 Goal 42 3.3 Seeing Waste (Nonvalue-Adding Activities) 43 3.3.1 Reserve Capacity 45 3.3.2 Excess Application Capacity 46 3.3.3 Excess Online Infrastructure Capacity 46 3.3.4 Excess Physical Infrastructure Capacity 46 3.3.5 Inadequate Capacity 47 3.3.6 Infrastructure Overhead 48 3.3.7 Capacity Management Overhead 48 3.3.8 Resource Overhead 49 3.3.9 Power Management Overhead 50 3.3.10 Workload Migration 50 3.3.11 Complexity Overhead 51 3.3.12 Resource Allocation Failure 51 3.3.13 Leaking and Lost Resources 53 3.3.14 Waste Heat 53 3.3.15 Carbon Footprint 54 3.4 Key Principles 54 3.4.1 Move toward Flow 55 3.4.2 Pull versus Push 55 3.4.3 Level the Workload 55 3.4.4 Stop and Fix Problems 55 3.4.5 Master Practices 56 3.4.6 Visual Management 57 3.4.7 Use Well-Tested Technology 57 3.4.8 Take a Long-Term Perspective 58 3.4.9 Grow, Learn, and Teach Others 58 3.4.10 Develop Exceptional People 58 3.4.11 Partners Help Each Other Improve 58 3.4.12 Go See 59 3.4.13 Implement Rapidly 59 3.4.14 Become a Learning Organization 59 3.5 Pillar: Respect 59 3.6 Pillar: Continuous Improvement 61 3.7 Foundation 62 3.8 Cadence 62 3.9 Lean Capacity Management Philosophy 63 3.10 Chapter Review 64 4. Lean Cloud Capacity Management Strategy 67 4.1 Lean Application Service Provider Strategy 68 4.1.1 User Workload Placement 71 4.1.2 Application Performance Management 73 4.2 Lean Infrastructure Service Provider Strategies 73 4.2.1 Physical Resource Capacity Management 76 4.3 Full Stream Optimization 77 4.4 Chapter Review 79 5. Electric Power Generation as Cloud Infrastructure Analog 81 5.1 Power Generation as a Cloud Infrastructure Analog 81 5.2 Business Context 83 5.3 Business Structure 86 5.4 Technical Similarities 88 5.5 Impedance and Fungibility 91 5.6 Capacity Ratings 94 5.7 Bottled Capacity 95 5.8 Location of Production Considerations 95 5.9 Demand Management 97 5.10 Demand and Reserves 98 5.11 Service Curtailment 99 5.12 Balance and Grid Operations 100 5.13 Chapter Review 103 6. Application Capacity Management as an Inventory Management Problem 105 6.1 The Application Capacity Management Service Delivery Chain 105 6.2 Traditional Application Service Production Chain 107 6.3 Elasticity and Demand-Driven Capacity Management 108 6.4 Application Service as Retail Analog 110 6.4.1 Locational Consideration 112 6.4.2 Inventory and Capacity 112 6.4.3 Service Level 113 6.4.4 Inventory Carrying Costs 114 6.4.5 Inventory Decision, Planning, and Ordering 115 6.4.6 Agility 118 6.4.7 Changing Consumption Patterns 118 6.5 Chapter Review 118 7. Lean Demand Management 119 7.1 Infrastructure Demand Management Techniques 120 7.1.1 Resource Scheduling 121 7.1.2 Resource Curtailment 121 7.1.3 Mandatory Demand Shaping 122 7.1.4 Voluntary Demand Shaping 123 7.1.5 Scheduling Maintenance Actions 123 7.1.6 Resource Pricing 123 7.2 Application Demand Management Techniques 124 7.2.1 Queues and Buffers 124 7.2.2 Load Balancers 124 7.2.3 Overload Controls 125 7.2.4 Explicit Demand Management Actions 125 7.2.5 Scheduling Maintenance Actions 125 7.2.6 User Pricing Strategies 126 7.3 Full Stream Analysis Methodology 126 7.3.1 Analyze Applications' Natural Demand Patterns 127 7.3.2 Analyze Applications' Tolerances 128 7.3.3 Create Attractive Infrastructure Pricing Models 129 7.3.4 Deploy Optimal Infrastructure Demand Management Models 130 7.4 Chapter Review 131 8. Lean Reserves 133 8.1 What Is Reserve Capacity? 133 8.2 Uses of Reserve Capacity 135 8.2.1 Random Demand Peaks 135 8.2.2 Component or Resource Failure 136 8.2.3 Infrastructure Element Failure 136 8.2.4 Infrastructure Resource Curtailment or Demand Management Action 137 8.2.5 Demand Exceeding Forecast 137 8.2.6 Lead Time Demand 137 8.2.7 Catastrophic Failures and Force Majeure Events 139 8.3 Reserve Capacity as a Feature 139 8.4 Types of Reserve Capacity 140 8.4.1 Automatic Infrastructure Power Management Controls 140 8.4.2 Utilize Application Reserve Capacity 141 8.4.3 Place/Migrate Demand into Underutilized Capacity 141 8.4.4 Grow Online Capacity 141 8.4.5 Service Curtailment/Degradation 141 8.4.6 Mandatory Demand Shaping 141 8.4.7 Voluntary Demand Shaping 142 8.4.8 Emergency Reserves 142 8.5 Limits of Reserve Capacity 144 8.6 Ideal Reserve 144 8.6.1 Normal (Co-located) Reserve 144 8.6.2 Emergency (Geographically Distributed) Reserve 146 8.7 Chapter Review 147 9. Lean Infrastructure Commitment 149 9.1 Unit Commitment and Infrastructure Commitment 150 9.2 Framing the Unit Commitment Problem 151 9.3 Framing the Infrastructure Commitment Problem 153 9.4 Understanding Element Startup Time 155 9.5 Understanding Element Shutdown Time 157 9.6 Pulling It All Together 160 9.7 Chapter Review 166 10. Lean Cloud Capacity Management Performance Indicators 167 10.1 Perfect Capacity Metrics 168 10.2 Capacity Management Metrics 172 10.3 Infrastructure Commitment Metrics 173 10.4 Waste Metrics 174 10.4.1 Reserve Capacity Waste Metrics 174 10.4.2 Excess Application Capacity Metrics 175 10.4.3 Excess Online Infrastructure Capacity Metrics 175 10.4.4 Excess Physical Infrastructure Capacity Metrics 175 10.4.5 Inadequate Capacity Metrics 175 10.4.6 Infrastructure Overhead Waste Metrics 176 10.4.7 Capacity Management Overhead Waste Metrics 176 10.4.8 Resource Overhead Waste Metrics 176 10.4.9 Power Management Overhead Waste Metrics 177 10.4.10 Workload Migration Metrics 177 10.4.11 Complexity Overhead Metrics 178 10.4.12 Resource Allocation Failure Metrics 178 10.4.13 Leaking and Lost Resources 179 10.4.14 Waste Heat Metrics 179 10.4.15 Carbon Footprint Metrics 180 10.5 Key Principle Indicators 180 10.6 Cost of Poor Quality 181 10.7 Metrics and Service Boundaries 182 10.8 Measurements and Maturity 183 10.9 Chapter Review 185 11. Summary 187 11.1 Cloud Computing as a Service Delivery Chain 187 11.2 Lean Cloud Computing 190 11.3 Reimagining Cloud Capacity 192 11.4 Lean Demand Management 195 11.5 Lean Reserves 197 11.6 Lean Infrastructure Service Provider Considerations 198 11.7 Lean Application Service Provider Considerations 198 11.8 Lean Infrastructure Commitment 199 11.9 Visualizing Perfect Capacity 201 11.10 Lean Cloud Computing Metrics 203 11.11 Concluding Remarks 204 References 207 About the Author 211 Index 213

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Book SynopsisPresentsinformationto create a trade-off analysis framework for use in government and commercial acquisition environments This book presents a decision management process based on decision theory and cost analysis best practices aligned with the ISO/IEC 15288, the Systems Engineering Handbook, and the Systems Engineering Body of Knowledge. It provides a sound trade-off analysis framework to generate the tradespace and evaluate value and risk to support system decision-making throughout the life cycle. Trade-off analysis and risk analysis techniques are examined. The authors present an integrated value trade-off and risk analysis framework based on decision theory. These trade-off analysis concepts are illustrated in the different life cycle stages using multiple examples from defense and commercial domains. Provides techniques to identify and structure stakeholder objectives and creative, doable alternatives Presents the advantages and disadvantagTable of ContentsList of Contributors xix About the Authors xxi Foreword xxxi Preface xxxiii Acknowledgments xli About the Companion Website xlv 1 Introduction to Trade-off Analysis 1Gregory S. Parnell, Matthew Cilli, Azad M. Madni and Garry Roedler 1.1 Introduction 2 1.2 Trade-off Analyses Throughout the Life Cycle 3 1.3 Trade-off Analysis to Identify System Value 3 1.4 Trade-off Analysis to Identify System Uncertainties and Risks 6 1.5 Trade-off Analyses can Integrate Value and Risk Analysis 6 1.6 Trade-off Analysis in the Systems Engineering Decision Management Process 8 1.7 Trade-off Analysis Mistakes of Omission and Commission 9 1.7.1 Mistakes of Omission 12 1.7.2 Mistakes of Commission 15 1.7.3 Impacts of the Trade-Off Analysis Mistakes 18 1.8 Overview of the Book 20 1.8.1 Illustrative Examples and Techniques Used in the Book 24 1.9 Key Terms 24 1.10 Exercises 25 References 26 2 A Conceptual Framework and Mathematical Foundation for Trade-Off Analysis 29Gregory S. Parnell, Azad M. Madni and Robert F. Bordley 2.1 Introduction 29 2.2 Trade-Off Analysis Terms 30 2.3 Influence Diagram of the Tradespace 31 2.3.1 Stakeholder Needs System Functions and Requirements 33 2.3.2 Objectives 33 2.3.3 System Alternatives 34 2.3.4 Uncertainty 36 2.3.5 Preferences and Evaluation of Alternatives 37 2.3.6 Resource Analysis 44 2.3.7 An Integrated Trade-Off Analyses 44 2.4 Tradespace Exploration 46 2.5 Summary 46 2.6 Key Words 47 2.7 Exercises 48 References 48 3 Quantifying Uncertainty 51Robert F. Bordley 3.1 Sources of Uncertainty in Systems Engineering 51 3.2 The Rules of Probability and Human Intuition 52 3.3 Probability Distributions 56 3.3.1 Calculating Probabilities from Experiments 56 3.3.2 Calculating Complex Probabilities from Simpler Probabilities 58 3.3.3 Calculating Probabilities Using Parametric Distributions 59 3.3.4 Applications of Parametric Probability Distributions 62 3.4 Estimating Probabilities 66 3.4.1 Using Historical Data 66 3.4.2 Using Human Judgment 68 3.4.3 Biases in Judgment 70 3.5 Modeling Using Probability 72 3.5.1 Bayes Nets 72 3.5.2 Monte Carlo Simulation 75 3.5.3 Monte Carlo Simulation with Dependent Uncertainties 76 3.5.4 Monte Carlo Simulation with Partial Information on Output Values 77 3.5.5 Variations on Monte Carlo Simulation 78 3.5.6 Sensitivity Analysis 78 3.6 Summary 81 3.7 Key Terms 81 3.8 Exercises 83 References 86 4 Analyzing Resources 91Edward A. Pohl, Simon R. Goerger and Kirk Michealson 4.1 Introduction 91 4.2 Resources 92 4.2.1 People 92 4.2.2 Facilities 95 4.2.3 Costs 95 4.2.4 Resource Space 99 4.3 Cost Analysis 99 4.3.1 Cost Estimation 102 4.3.2 Cost Estimation Techniques 108 4.3.3 Learning Curves 120 4.3.4 Net Present Value 125 4.3.5 Monte Carlo Simulation 130 4.3.6 Sensitivity Analysis 134 4.4 Affordability Analysis 135 4.4.1 Background 136 4.4.2 The Basics of Affordability Analysis Are Not Difficult 137 4.4.3 DoD Comparison of Cost Analysis and Affordability Analysis 138 4.4.4 Affordability Analysis Definitions 139 4.4.5 “Big A” Affordability Analysis Process Guide 141 4.5 Key Terms 147 4.6 Excercises 149 References 152 5 Understanding Decision Management 155Matthew Cilli and Gregory S. Parnell 5.1 Introduction 155 5.2 Decision Process Context 156 5.3 Decision Process Activities 157 5.3.1 Frame Decision 159 5.3.2 Develop Objectives and Measures 163 5.3.3 Generate Creative Alternatives 171 5.3.4 Assess Alternatives via Deterministic Analysis 180 5.3.5 Synthesize Results 183 5.3.6 Develop Multidimensional Value Model 187 5.3.7 Identify Uncertainty and Conduct Probabilistic Analysis 190 5.3.8 Assess Impact of Uncertainty 192 5.3.9 Improve Alternatives 196 5.3.10 Communicating Trade-Offs 197 5.3.11 Present Recommendation and Implementation Plan 197 5.4 Summary 199 5.5 Key Terms 199 5.6 Exercises 200 References 201 6 Identifying Opportunities 203Donna H. Rhodes and Simon R. Goerger 6.1 Introduction 203 6.2 Knowledge 205 6.2.1 Domain Knowledge 205 6.2.2 Technical Knowledge 205 6.2.3 Business Knowledge 205 6.2.4 Expert Knowledge 206 6.2.5 Stakeholder Knowledge 206 6.3 Decision Traps 207 6.4 Techniques 210 6.4.1 Interviews 210 6.4.2 Focus Groups 213 6.4.3 Surveys 215 6.5 Tools 219 6.5.1 Concept Map 219 6.5.2 System Boundary 220 6.5.3 Decision Hierarchy 220 6.5.4 Issues List 221 6.5.5 Vision Statement 221 6.5.6 Influence Diagram 222 6.5.7 Selecting Appropriate Tools and Techniques 223 6.6 Illustrative Examples 223 6.6.1 Commercial 223 6.6.2 Defense 226 6.7 Key Terms 228 6.8 Exercises 230 References 230 7 Identifying Objectives and Value Measures 233Gregory S. Parnell and William D. Miller 7.1 Introduction 233 7.2 Value-Focused Thinking 234 7.2.1 Four Major VFT Ideas 235 7.2.2 Benefits of VFT 235 7.3 Shareholder and Stakeholder Value 236 7.3.1 Private Company Example 237 7.3.2 Government Agency Example 237 7.4 Challenges in Identifying Objectives 238 7.5 Identifying the Decision Objectives 239 7.5.1 Questions to Help Identify Decision Objectives 239 7.5.2 How to Get Answers to the Questions 240 7.6 The Financial or Cost Objective 241 7.6.1 Financial Objectives for Private Companies 241 7.6.2 Cost Objective for Public Organizations 242 7.7 Developing Value Measures 243 7.8 Structuring Multiple Objectives 243 7.8.1 Value Hierarchies 244 7.8.2 Techniques for Developing Value Hierarchies 245 7.8.3 Value Hierarchy Best Practices 247 7.8.4 Cautions about Cost and Risk Objectives 248 7.9 Illustrative Examples 248 7.9.1 Military Illustrative Example 248 7.9.2 Homeland Security Illustrative Example 250 7.10 Summary 250 7.11 Key Terms 252 7.12 Exercises 253 References 255 8 Developing and Evaluating Alternatives 257C. Robert Kenley, Clifford Whitcomb and Gregory S. Parnell 8.1 Introduction 257 8.2 Overview of Decision-making Creativity and Teams 258 8.2.1 Approaches to Decision-Making 258 8.2.2 Cognitive Methods for Creating Alternatives 260 8.2.3 Key Concepts for Building and Operating Teams 260 8.3 Alternative Development Techniques 263 8.3.1 Structured Creativity Methods 263 8.3.2 Morphological Box 266 8.3.3 Pugh Method for Alternative Generation 270 8.3.4 TRIZ for Alternative Development 271 8.4 Assessment of Alternative Development Techniques 275 8.5 Alternative Evaluation Techniques 276 8.5.1 Decision-Theory-Based Approaches 276 8.5.2 Pugh Method for Alternative Evaluation 276 8.5.3 Axiomatic Approach to Design (AAD) 277 8.5.4 TRIZ for Alternative Evaluation 280 8.5.5 Design of Experiments (DOE) 280 8.5.6 Taguchi Approach 282 8.5.7 Quality Function Deployment (QFD) 283 8.5.8 Analytic Hierarchy Process AHP 287 8.6 Assessment of Alternative Evaluation Techniques 290 8.7 Key Terms 290 8.8 Exercises 290 References 293 9 An Integrated Model for Trade-Off Analysis 297Alexander D. MacCalman, Gregory S. Parnell and Sam Savage 9.1 Introduction 297 9.2 Conceptual Design Example 298 9.3 Integrated Approach Influence Diagram 300 9.3.1 Decision Nodes 300 9.3.2 Uncertainty Nodes 303 9.3.3 Constant Node 310 9.3.4 Value Nodes 314 9.4 Other Types of Trade-Off Analysis 322 9.5 Simulation Tools 322 9.5.1 Monte Carlo Simulation Proprietary Add-Ins 324 9.5.2 The Discipline of Probability Management 324 9.5.3 SIPmathTM Tool in Native Excel 324 9.5.4 Model Building Steps 325 9.6 Summary 329 9.7 Key Terms 330 9.8 Exercises 331 References 335 10 Exploring Concept Trade-Offs 337Azad M. Madni and Adam M. Ross 10.1 Introduction 337 10.1.1 Key Concepts Concept Trade-Offs and Concept Exploration 341 10.2 Defining the Concept Space and System Concept of Operations 345 10.3 Exploring the Concept Space 346 10.3.1 Storytelling-Enabled Tradespace Exploration 346 10.3.2 Decisions and Outcomes 347 10.3.3 Contingent Decision-Making 347 10.4 Trade-off Analysis Frameworks 348 10.5 Tradespace and System Design Life Cycle 349 10.6 From Point Trade-offs to Tradespace Exploration 351 10.7 Value-based Multiattribute Tradespace Analysis 351 10.7.1 Tradespace Exploration and Sensitivity Analysis 353 10.7.2 Tradespace Exploration and Uncertainty 354 10.7.3 Tradespace Exploration with Spiral Development 356 10.7.4 Tradespace Exploration in Relation to Optimization and Decision Theory 356 10.8 Illustrative Example 359 10.8.1 Step 1: Determine Key Decision-Makers 359 10.8.2 Step 2: Scope and Bound the Mission 360 10.8.3 Step 3: Elicit Attributes and Utilities (Preference Capture) 360 10.8.4 Step 4: Define Design Vector Elements (Concept Generation) 362 10.8.5 Step 5: Develop Model(s) (Evaluation) 362 10.8.6 Step 6: Generate the Tradespace (Computation) 364 10.8.7 Step 7: Explore the Tradespace (Analysis and Synthesis) 365 10.9 Conclusions 369 10.10 Key Terms 371 10.11 Exercises 372 References 372 11 Architecture Evaluation Framework 377James N. Martin 11.1 Introduction 377 11.1.1 Architecture in the Decision Space 378 11.1.2 Architecture Evaluation 379 11.1.3 Architecture Views and Viewpoints 380 11.1.4 Stakeholders 382 11.1.5 Stakeholder Concerns 382 11.1.6 Architecture versus Design 383 11.1.7 On the Uses of Architecture 384 11.1.8 Standardizing on an Architecture Evaluation Strategy 384 11.2 Key Considerations in Evaluating Architectures 385 11.2.1 Plan-Driven Evaluation Effort 386 11.2.2 Objectives-Driven Evaluation 387 11.2.3 Assessment versus Analysis 387 11.3 Architecture Evaluation Elements 389 11.3.1 Architecture Evaluation Approach 389 11.3.2 Architecture Evaluation Objectives 390 11.3.3 Evaluation Approach Examples 391 11.3.4 Value Assessment Methods 391 11.3.5 Value Assessment Criteria 393 11.3.6 Architecture Analysis Methods 394 11.4 Steps in an Architecture Evaluation Process 396 11.5 Example Evaluation Taxonomy 398 11.5.1 Business Impact Factors 398 11.5.2 Mission Impact Factors 398 11.5.3 Architecture Attributes 399 11.6 Summary 400 11.7 Key Terms 400 11.8 Exercises 402 References 402 12 Exploring the Design Space 405Clifford Whitcomb and Paul Beery 12.1 Introduction 405 12.2 Example 1: Liftboat 406 12.2.1 Liftboat Fractional Factorial Design of Experiments 406 12.2.2 Liftboat Design Trade-Off Space 409 12.2.3 Liftboat Uncertainty Analysis 411 12.2.4 Liftboat Example Summary 411 12.3 Example 2: Cruise Ship Design 411 12.3.1 Cruise Ship Taguchi Design of Experiments 411 12.3.2 Cruise Ship Design Trade-Off Space 412 12.3.3 Cruise Ship Example Summary 416 12.4 Example 3: NATO Naval Surface Combatant Ship 417 12.4.1 NATO Surface Combatant Ship Stakeholder Need 418 12.4.2 NATO Surface Combatant Ship Box–Behnken Design of Experiments 420 12.4.3 NATO Surface Combatant Ship Cost-Effectiveness Trade-Off 421 12.4.4 NATO Surface Combatant Ship Design Tradespace 421 12.4.5 NATO Surface Combatant Ship Design Trade-Off 422 12.4.6 NATO Surface Combatant Ship Trade-Off Summary 430 12.5 Key Terms 431 12.6 Exercises 433 References 435 13 Sustainment Related Models and Trade Studies 437John E. MacCarthy and Andres Vargas 13.1 Introduction 437 13.2 Availability Modeling and Trade Studies 439 13.2.1 FMDS Background 439 13.2.2 FMDS Availability Trade Studies 449 13.2.3 Section Synopsis 453 13.3 Sustainment Life Cycle Cost Modeling and Trade Studies14 454 13.3.1 The Total System Life Cycle Model 454 13.3.2 The O&S Cost Model 456 13.3.3 Life Cycle Cost Trade Study 459 13.4 Optimization in Availability Trade Studies 464 13.4.1 Setting Up the Optimization Problem 464 13.4.2 Instantiating the Optimization Model 465 13.4.3 Discussion of the Optimization Model Results 468 13.4.4 Deterministic Sensitivity Analysis 469 13.5 Monte Carlo Modeling 471 13.5.1 Input Probability Distributions for the Monte Carlo Model 471 13.5.2 Monte Carlo Simulation Results 472 13.5.3 Stochastic Sensitivity Analysis 473 13.6 Chapter Summary 475 13.7 Key Terms 476 13.8 Exercises 478 References 482 14 Performing Programmatic Trade-Off Analyses 483Gina Guillaume-Joseph and John E. MacCarthy 14.1 Introduction 483 14.2 System Acceptance Decisions and Trade Studies 485 14.2.1 Acceptance Decision Framework 486 14.2.2 Calculating the Confidence That a System Is “Good” 491 14.2.3 Acceptance Test Design and Trade Studies 493 14.2.4 A “Delay Fix and Test” Cost Model 499 14.2.5 The Integrated Decision Model 504 14.2.6 Conclusions 511 14.3 Product Cancelation Decision Trade Study 512 14.3.1 Introduction 512 14.3.2 Significance 513 14.3.3 Defining Failure 514 14.3.4 Developing the Predictive Model 519 14.3.5 Research Results 522 14.3.6 Model Implementation In Industry 528 14.3.7 Predictive Model Deployment in Industry 530 14.3.8 When the Decision Has Been Made to Cancel the System 536 14.3.9 Conclusion 537 14.4 Product Retirement Decision Trade Study 538 14.4.1 Introduction 538 14.4.2 Legacy HR Systems 539 14.4.3 The US NAVY Retirement and Decommission Program for Nuclear-Powered Vessels 544 14.4.4 Decision Analysis for Decommissioning Offshore Oil and Gas Platforms in California 551 14.4.5 System Retirement and Decommissioning Strategy 559 14.4.6 Conclusion 561 14.5 Key Terms 562 14.6 Exercises 564 References 566 15 Summary and Future Trends 571Gregory S. Parnell and Simon R. Goerger 15.1 Introduction 571 15.2 Major Trade-Off Analysis Themes 572 15.2.1 Use Standard Systems Engineering Terminology 572 15.2.2 Avoid the Mistakes of Omission and Commission 572 15.2.3 Use a Decision Management Framework 572 15.2.4 Use Decision Analysis as the Mathematical Foundation 573 15.2.5 Explicitly Define the Decision Opportunity 573 15.2.6 Identify and Structure Decision Objectives and Measures 574 15.2.7 Identify Creative Doable Alternatives 574 15.2.8 Use the Most Appropriate Modeling and Simulation Technique for the Life Cycle Stage 575 15.2.9 Include Resource Analysis in the Trade-Off Analysis 575 15.2.10 Explicitly Consider Uncertainty 575 15.2.11 Identify the Cost Value Schedule and Risk Drivers 575 15.2.12 Provide an Integrated Framework for Cost Value and Risk Analyses 576 15.3 Future of Trade-Off Analysis 576 15.3.1 Education and Training of Systems Engineers 577 15.3.2 Systems Engineering Methodologies and Tools 577 15.3.3 Emergent Tradespace Factors 580 15.4 Summary 581 References 581 Index 583

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Book SynopsisThis book presents and discusses strategies for the design and implementation of common-mode suppressed balanced microwave filters, including, narrowband, wideband, and ultra-wideband filters This book examines differential-mode, or balanced, microwave filters by discussing several implementations of practical realizations of these passive components. Topics covered include selective mode suppression, designs based on distributed and semi-lumped approaches, multilayer technologies, defect ground structures, coupled resonators, metamaterials, interference techniques, and substrate integrated waveguides, among others. Divided into five parts, Balanced Microwave Filters begins with an introduction that presents the fundamentals of balanced lines, circuits, and networks. Part 2 covers balanced transmission lines with common-mode noise suppression, including several types of common-mode filters and the application of such filters to enhance common-mode suppression in balanced bandpass filteTable of ContentsLIST OF CONTRIBUTORS xix PREFACE xxiii PART 1 INTRODUCTION 1 1 INTRODUCTION TO BALANCED TRANSMISSION LINES, CIRCUITS, AND NETWORKS 3Ferran Martín, Jordi Naqui, Francisco Medina, Lei Zhu, and Jiasheng Hong 1.1 Introduction 3 1.2 Balanced Versus Single-Ended Transmission Lines and Circuits 4 1.3 Common-Mode Noise 5 1.4 Fundamentals of Differential Transmission Lines 6 1.4.1 Topology 6 1.4.2 Propagating Modes 8 1.4.2.1 Even and Odd Mode 8 1.4.2.2 Common and Differential Mode 11 1.5 Scattering Parameters 13 1.5.1 Single-Ended S-Parameters 13 1.5.2 Mixed-Mode S-Parameters 16 1.6 Summary 19 References 19 PART 2 BALANCED TRANSMISSION LINES WITH COMMON-MODE NOISE SUPPRESSION 21 2 STRATEGIES FOR COMMON-MODE SUPPRESSION IN BALANCED LINES 23Ferran Martín, Paris Vélez, Armando Fernández-Prieto, Jordi Naqui, Francisco Medina, and Jiasheng Hong 2.1 Introduction 23 2.2 Selective Mode Suppression in Differential Transmission Lines 25 2.3 Common-Mode Suppression Filters Based on Patterned Ground Planes 27 2.3.1 Common-Mode Filter Based on Dumbbell-Shaped Patterned Ground Plane 27 2.3.2 Common-Mode Filter Based on Complementary Split Ring Resonators (CSRRs) 30 2.3.3 Common-Mode Filter Based on Defected Ground Plane Artificial Line 40 2.3.4 Common-Mode Filter Based on C-Shaped Patterned Ground Structures 44 2.4 Common-Mode Suppression Filters Based on Electromagnetic Bandgaps (EBGs) 49 2.4.1 Common-Mode Filter Based on Nonuniform Coupled Lines 50 2.4.2 Common-Mode Filter Based on Uniplanar Compact Photonic Bandgap (UC-PBG) Structure 55 2.5 Other Approaches for Common-Mode Suppression 55 2.6 Comparison of Common-Mode Filters 60 2.7 Summary 61 Appendix 2.A: Dispersion Relation for Common-Mode Rejection Filters with Coupled CSRRs or DS-CSRRs 61 Appendix 2.B: Dispersion Relation for Common-Mode Rejection Filters with Coupled Patches Grounded through Inductive Strips 64 References 65 3 COUPLED-RESONATOR BALANCED BANDPASS FILTERS WITH COMMON-MODE SUPPRESSION DIFFERENTIAL LINES 73Armando Fernández-Prieto, Jordi Naqui, Jesús Martel, Ferran Martín, and Francisco Medina 3.1 Introduction 73 3.2 Balanced Coupled-Resonator Filters 74 3.2.1 Single-Band Balanced Bandpass Filter Based on Folded Stepped-Impedance Resonators 75 3.2.2 Balanced Filter Loaded with Common-Mode Rejection Sections 79 3.2.3 Balanced Dual-Band Bandpass Filter Loaded with Common-Mode Rejection Sections 82 3.3 Summary 88 References 88 PART 3 WIDEBAND AND ULTRA-WIDEBAND (UWB) BALANCED BAND PASS FILTERS WITH INTRINSIC COMMON-MODE SUPPRESSION 91 4 WIDEBAND AND UWB BALANCED BANDPASS FILTERS BASED ON BRANCH-LINE TOPOLOGY 93Teck Beng Lim and Lei Zhu 4.1 Introduction 93 4.2 Branch-Line Balanced Wideband Bandpass Filter 97 4.3 Balanced Bandpass Filter for UWB Application 105 4.4 Balanced Wideband Bandpass Filter with Good Common-Mode Suppression 111 4.5 Highly Selective Balanced Wideband Bandpass Filters 116 4.6 Summary 131 References 131 5 WIDEBAND AND UWB COMMON-MODE SUPPRESSED DIFFERENTIAL-MODE FILTERS BASED ON COUPLED LINE SECTIONS 135Qing-Xin Chu, Shi-Xuan Zhang, and Fu-Chang Chen 5.1 Balanced UWB Filter by Combining UWB BPF with UWB BSF 135 5.2 Balanced Wideband Bandpass Filter Using Coupled Line Stubs 142 5.3 Balanced Wideband Filter Using Internal Cross-Coupling 148 5.4 Balanced Wideband Filter Using Stub-Loaded Ring Resonator 155 5.5 Balanced Wideband Filter Using Modified Coupled Feed Lines and Coupled Line Stubs 161 5.6 Summary 173 References 174 6 WIDEBAND DIFFERENTIAL CIRCUITS USING T-SHAPED STRUCTURES AND RING RESONATORS 177Wenquan Che and Wenjie Feng 6.1 Introduction 177 6.2 Wideband Differential Bandpass Filters Using T-Shaped Resonators 179 6.2.1 Mixed-Mode S-Parameters for Four-Port Balanced Circuits 179 6.2.2 T-Shaped Structures with Open/Shorted Stubs 184 6.2.2.1 T-Shaped Structure with Shorted Stubs 184 6.2.2.2 T-Shaped Structure with Open Stubs 185 6.2.3 Wideband Bandpass Filters without Cross Coupling 187 6.2.3.1 Differential-Mode Excitation 189 6.2.3.2 Common-Mode Excitation 191 6.2.4 Wideband Bandpass Filter with Cross Coupling 193 6.3 Wideband Differential Bandpass Filters Using Half-/Full-Wavelength Ring Resonators 201 6.3.1 Differential Filter Using Half-Wavelength Ring Resonators 201 6.3.2 Differential Filter Using Full-Wavelength Ring Resonators 206 6.3.3 Differential Filter Using Open/Shorted Coupled Lines 215 6.3.4 Comparisons of Several Wideband Balanced Filters Based on Different Techniques 220 6.4 Wideband Differential Networks Using Marchand Balun 223 6.4.1 S-Parameter for Six-Port Differential Network 223 6.4.2 Wideband In-Phase Differential Network 227 6.4.3 Wideband Out-of-Phase Differential Network 236 6.5 Summary 244 References 245 7 UWB AND NOTCHED-BAND UWB DIFFERENTIAL FILTERS USING MULTILAYER AND DEFECTED GROUND STRUCTURES (DGSS) 249Jian-Xin Chen, Li-Heng Zhou, and Quan Xue 7.1 Conventional Multilayer Microstrip-to-Slotline Transition (MST) 250 7.2 Differential MST 251 7.2.1 Differential MST with a Two-Layer Structure 251 7.2.2 Differential MST with Three-Layer Structure 252 7.3 UWB Differential Filters Based on the MST 253 7.3.1 Differential Wideband Filters Based on the Conventional MST 253 7.3.2 Differential Wideband Filters Based on the Differential MST 255 7.4 Differential Wideband Filters Based on the Strip-Loaded Slotline Resonator 262 7.4.1 Differential Wideband Filters Using Triple-Mode Slotline Resonator 265 7.4.2 Differential Wideband Filters Using Quadruple-Mode Slotline Resonator 267 7.5 UWB Differential Notched-Band Filter 270 7.5.1 UWB Differential Notched-Band Filter Based on the Traditional MST 270 7.5.2 UWB Differential Notched-Band Filter Based on the Differential MST 272 7.6 Differential UWB Filters with Enhanced Stopband Suppression 277 7.7 Summary 280 References 281 8 APPLICATION OF SIGNAL INTERFERENCE TECHNIQUE TO THE IMPLEMENTATION OF WIDEBAND DIFFERENTIAL FILTERS 283Wei Qin and Quan Xue 8.1 Basic Concept of the Signal Interference Technique 283 8.1.1 Fundamental Theory 284 8.1.2 One Filter Example Based on Ring Resonator 287 8.1.3 Simplified Circuit Model 288 8.2 Signal Interference Technique for Wideband Differential Filters 290 8.2.1 Circuit Model of Wideband Differential Bandpass Filter 290 8.2.2 S-Matrix for Differential Bandpass Filters 292 8.3 Several Designs of Wideband Differential Bandpass Filters 293 8.3.1 Differential Bandpass Filter Based on Wideband Marchand Baluns 293 8.3.2 Differential Bandpass Filter Based on π-Type UWB 180 Phase Shifters 299 8.3.3 Differential Bandpass Filter Based on DSPSL UWB 180 Phase Inverter 302 8.3.3.1 Differential-Mode Analysis 305 8.3.3.2 Common-Mode Analysis 305 8.3.3.3 Filter Design and Measurement 308 8.4 Summary 308 References 309 9 WIDEBAND BALANCED FILTERS BASED ON MULTI-SECTION MIRRORED STEPPED IMPEDANCE RESONATORS (SIRs) 311 Ferran Martín, Jordi Selga, Paris Vélez, Marc Sans, Jordi Bonache, Ana Rodríguez, Vicente E. Boria, Armando Fernández-Prieto, and Francisco Medina 9.1 Introduction 311 9.2 The Multi-Section Mirrored Stepped Impedance Resonator (SIR) 312 9.3 Wideband Balanced Bandpass Filters Based on 7-Section Mirrored SIRs Coupled Through Admittance Inverters 317 9.3.1 Finding the Optimum Filter Schematic 319 9.3.2 Layout Synthesis 325 9.3.2.1 Resonator Synthesis 325 9.3.2.2 Determination of the Line Width 327 9.3.2.3 Optimization of the Line Length (Filter Cell Synthesis) 327 9.3.3 A Seventh-Order Filter Example 330 9.3.4 Comparison with Other Approaches 334 9.4 Compact Ultra-Wideband (UWB) Balanced Bandpass Filters Based on 5-Section Mirrored SIRs and Patch Capacitors 336 9.4.1 Topology and Circuit Model of the Series Resonators 337 9.4.2 Filter Design 341 9.4.3 Comparison with Other Approaches 345 9.5 Summary 346 Appendix 9.A: General Formulation of Aggressive Space Mapping (ASM) 347 References 349 10 METAMATERIAL-INSPIRED BALANCED FILTERS 353Ferran Martín, Paris Vélez, Ali Karami-Horestani, Francisco Medina, and Christophe Fumeaux 10.1 Introduction 353 10.2 Balanced Bandpass Filters Based on Open Split Ring ResonatorS (OSRRS) and Open Complementary Split Ring Resonators (OCSRRS) 354 10.2.1 Topology of the OSRR and OCSRR 354 10.2.2 Filter Design and Illustrative Example 356 10.3 Balanced Filters Based on S-Shaped Complementary Split Ring Resonators (S-CSRRs) 363 10.3.1 Principle for Balanced Bandpass Filter Design and Modeling 365 10.3.2 Illustrative Example 367 10.4 Summary 369 References 369 11 WIDEBAND BALANCED FILTERS ON SLOTLINE RESONATOR WITH INTRINSIC COMMON-MODE REJECTION 373Xin Guo, Lei Zhu, and Wen Wu 11.1 Introduction 373 11.2 Wideband Balanced Bandpass Filter on Slotline MMR 375 11.2.1 Working Mechanism 375 11.2.2 Synthesis Method 378 11.2.3 Geometry and Layout 382 11.2.4 Fabrication and Experimental Verification 388 11.3 Wideband Balanced BPF on Strip-Loaded Slotline Resonator 392 11.3.1 Strip-Loaded Slotline Resonator 392 11.3.2 Wideband Balanced Bandpass Filters 396 11.3.2.1 Wideband Balanced BPF on Strip-Loaded Triple-Mode Slotline Resonator 397 11.3.2.2 Wideband Balanced BPF on Strip-Loaded Quadruple-Mode Slotline Resonator 403 11.4 Wideband Balanced Bandpass Filter on Hybrid MMR 408 11.4.1 Hybrid MMR 408 11.4.2 Wideband Balanced Bandpass Filters 416 11.5 Summary 420 References 420 PART 4 NARROWBAND AND DUAL-BAND BALANCED BANDPASS FILTERS WITH INTRINSIC COMMON-MODE SUPPRESSION 423 12 NARROWBAND COUPLED-RESONATOR BALANCED BANDPASS FILTERS AND DIPLEXERS 425Armando Fernández-Prieto, Francisco Medina, and Jesús Martel 12.1 Introduction 425 12.2 Coupled-Resonator Balanced Filters with Intrinsic Common-Mode Rejection 426 12.2.1 Loop and SIR Resonator Filters with Mixed Coupling 427 12.2.1.1 Quasi-elliptic Response BPF: First Example 428 12.2.1.2 Quasi-elliptic Response BPF: Second Example 434 12.2.2 Magnetically Coupled Open-Loop and FSIR Balanced Filters 439 12.2.2.1 Filters with Magnetic Coupling: First Example 439 12.2.2.2 Filters with Magnetic Coupling: Second Example 447 12.2.3 Interdigital Line Resonators Filters 449 12.2.3.1 ILR Filter Design Example 450 12.2.4 Dual-Mode and Dual-Behavior Resonators for Balanced Filter Design 451 12.2.4.1 Dual-Mode Square Patch Resonator Filters 453 12.2.4.2 Filters Based on Dual-Behavior Resonators 458 12.2.5 LTCC-Based Multilayer Balanced Filter 464 12.2.6 Balanced Bandpass Filters Based on Dielectric Resonators 466 12.3 Loaded Resonators for Common-Mode Suppression Improvement 469 12.3.1 Capacitively, Inductively, and Resistively Center-Loaded Resonators 470 12.3.1.1 Open-Loop UIR-Loaded Filter 470 12.3.1.2 Folded SIR Loaded Filter 476 12.3.2 Filters with Defected Ground Structures (DGS) 484 12.3.2.1 Control of the Transmission Zeros 488 12.3.3 Multilayer Loaded Resonators 490 12.3.3.1 Design Example 492 12.4 Coupled Line Balanced Bandpass Filter 493 12.4.1 Type-II Design Example 495 12.5 Balanced Diplexers 499 12.5.1 Unbalanced-to-Balanced Diplexer Based on Uniform Impedance Stub-Loaded Coupled Resonators 500 12.5.1.1 Resonator Geometry 500 12.5.1.2 Unbalanced-to-Balanced Diplexer Design 502 12.5.2 Example Two: Balanced-to-Balanced Diplexer Based on UIRs and Short-Ended Parallel-Coupled Lines 505 12.6 Summary 508 References 510 13 DUAL-BAND BALANCED FILTERS BASED ON LOADED AND COUPLED RESONATORS 515Jin Shi and Quan Xue 13.1 Dual-Band Balanced Filter with Loaded Uniform Impedance Resonators 516 13.1.1 Center-Loaded Uniform Impedance Resonator 516 13.1.2 Dual-Band Balanced Filter Using the Uniform Impedance Resonator with Center-Loaded Lumped Elements 520 13.1.3 Dual-Band Balanced Filter Using Stub-Loaded Uniform Impedance Resonators 526 13.2 Dual-Band Balanced Filter with Loaded Stepped-Impedance Resonators 528 13.2.1 Center-Loaded Stepped-Impedance Resonator 528 13.2.2 Dual-Band Balanced Filter Using Stepped-Impedance Resonators with Center-Loaded Lumped Elements 531 13.2.3 Dual-Band Balanced Filter Using Stub-Loaded Stepped-Impedance Resonators 535 13.3 Dual-Band Balanced Filter Based on Coupled Resonators 538 13.3.1 Dual-Band Balanced Filter with Coupled Stepped-Impedance Resonators 538 13.3.2 Dual-Band Balanced Filter with Coupled Stub-Loaded Short-Ended Resonators 542 13.4 Summary 546 References 547 14 DUAL-BAND BALANCED FILTERS IMPLEMENTED IN SUBSTRATE INTEGRATED WAVEGUIDE (SIW) TECHNOLOGY 549Wen Wu, Jianpeng Wang, and Chunxia Zhou 14.1 Substrate Integrated Waveguide (SIW) Cavity 550 14.2 Closely Proximate Dual-Band Balanced Filter Design 551 14.3 Dual-Band Balanced Filter Design Utilizing High-Order Modes in SIW Cavities 555 14.4 Summary 563 References 563 PART 5 OTHER BALANCED CIRCUITS 565 15 BALANCED POWER DIVIDERS/COMBINERS 567Lin-Sheng Wu, Bin Xia, and Jun-Fa Mao 15.1 Introduction 567 15.2 Balanced-to-Balanced Wilkinson Power Divider with Microstrip Line 569 15.2.1 Mixed-Mode Analysis 569 15.2.1.1 Mixed-Mode Scattering Matrix of a Balanced-to-Balanced Power Divider 569 15.2.1.2 Constraint Rules of Balanced-to-Balanced Power Divider 571 15.2.1.3 Odd- and Even-Mode Scattering Matrices of Balanced-to-Balanced Power Divider 572 15.2.2 A Transmission-Line Balanced-to-Balanced Power Divider 572 15.2.2.1 Even-Mode Circuit Model 572 15.2.2.2 Odd-Mode Circuit Model 573 15.2.2.3 Scattering Matrix of the Balanced-to-Balanced Power Divider 575 15.2.3 Theoretical Result 575 15.2.4 Simulated and Measured Results 576 15.3 Balanced-to-Balanced Gysel Power Divider with Half-Mode Substrate Integrated Waveguide (SIW) 580 15.3.1 Conversion from Single-Ended Circuit to Balanced Form 580 15.3.2 Half-Mode SIW Ring Structure 581 15.3.3 Results and Discussion 583 15.4 Balanced-to-Balanced Gysel Power Divider with Arbitrary Power Division 585 15.4.1 Analysis and Design 585 15.4.2 Results and Discussion 587 15.5 Balanced-to-Balanced Gysel Power Divider with Bandpass Filtering Response 590 15.5.1 Coupled-Resonator Circuit Model 590 15.5.2 Realization in Transmission Lines 591 15.5.2.1 Internal Coupling Coefficient 592 15.5.2.2 External Q Factor 594 15.5.3 Results and Discussion 595 15.6 Filtering Balanced-to-Balanced Power Divider with Unequal Power Division 598 15.7 Dual-Band Balanced-to-Balanced Power Divider 599 15.7.1 Analysis and Design 599 15.7.2 Results and Discussion 601 15.8 Summary 603 References 603 16 DIFFERENTIAL-MODE EQUALIZERS WITH COMMON-MODE FILTERING 607Tzong-Lin Wu and Chiu-Chih Chou 16.1 Introduction 607 16.2 Design Considerations 610 16.2.1 Equalizer Design 610 16.2.2 Common-Mode Filter Design 612 16.3 First Design 613 16.3.1 Proposed Topology 613 16.3.2 Odd-Mode Analysis 616 16.3.2.1 Equalizer Optimization in Time Domain 617 16.3.3 Even-Mode Analysis 623 16.3.4 Measurement Validation 628 16.4 Second Design 633 16.4.1 Proposed Circuit and Analysis 633 16.4.2 Realization and Measurement 637 16.4.2.1 Realization 637 16.4.2.2 Common-Mode Noise Suppression 638 16.4.2.3 Differential-Mode Equalization 640 16.5 Summary 641 References 641 INDEX 645

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Book SynopsisPresents a new, effective methodology in software size measurement Software size measurement is an extremely important and highly specialized aspect of the software life cycle.Table of ContentsPreface xi Acknowledgments xv About the Author xvii List of Acronyms xix About the Companion Websites xxv Part One FSSM: Introduction 1 Introduction to Functional Software Size Measurement 3 1.1 Introduction 3 1.2 Functional Size Measurement and Effort Estimation 3 1.3 Important Considerations for the Software Size Measurement and Effort Estimation 4 1.4 Introduction to the Functional Software Size Measurement Methodology with Effort Estimation and Performance Indication (FSSM) 10 1.5 Chapter Summary 12 Exercises 13 2 Synopsis of the Functional Software Size Measurement Methodology with Effort Estimation and Performance Indication (FSSM) 15 2.1 Salient Characteristics of the FSSM 15 2.2 Distinguishing Unique Key Features of the FSSM 20 2.3 Synoptic Description of the FSSM 22 2.4 Lists and Brief Descriptions of the FSSM Constituents 36 2.5 Source of Information for the FSSM Constituents 46 2.6 Examples 47 2.7 Chapter Summary 49 Exercises 49 Part Two FSSM: Software View 3 Software’s Measurable Components in the FSSM 53 3.1 Software’s Measurable Component (SMC) Description 53 3.2 Software’s Measurable Components (SMCs) Characteristics 56 3.3 Software’s Measurable Components (SMCs) Presence and Size 56 3.4 Examples 57 3.5 Chapter Summary 57 Exercises 58 4 Software Component’s Measurable Features in the FSSM 59 4.1 Software Component’s Measurable Feature (SCMF) Description 59 4.2 Usage of the Software Component’s Measurable Features (SCMFs) 71 4.3 Software Component’s Measurable Features (SCMFs) Presence and Quantity 72 4.4 Examples 72 4.5 Chapter Summary 74 Exercises 75 Part Three FSSM: Measurements 5 Software Component’s Feature Points in the FSSM 79 5.1 Software Component’s Feature Point (SCFP) Description 79 5.2 Usage of the Software Component’s Feature Points (SCFPs) 92 5.3 Software Component’s Feature Points (SCFPs) Presence and Quantity 92 5.4 Examples 93 5.5 Chapter Summary 95 Exercises 96 6 Software Component’s Feature Point Counts in the FSSM 97 6.1 Software Component’s Feature Point Count (SCFPC) Description 97 6.2 Counting Guidelines Flowchart for the Software Component’s Measurable Features (SCMFs) of the Software’s Measurable Component ‘Functionality Execution’ (CFE) 105 6.3 Some Specific Guidelines for the Software Component’s Feature Point (SCFP) Counting 105 6.4 Software Component’s Feature Point Counts (SCFPCs) Formation 110 6.5 Usage of the Software Component’s Feature Point Counts (SCFPCs) 110 6.6 Software Component’s Feature Point Counts (SCFPCs) Value 112 6.7 Examples 112 6.8 Chapter Summary 113 Exercises 114 7 Software Component’s Measurements through Software Component’s Feature Measurements in the FSSM 116 7.1 Software Component’s Measurement (SCM) and Software Component’s Feature Measurement (SCFM) Description 116 7.2 Software Component’s Measurement (SCM) and Software Component’s Feature Measurement (SCFM) Formulae 123 7.3 Examples 130 7.4 Chapter Summary 131 Exercises 133 Part Four FSSM: Estimations and Indications 8 Software Size Determination and Effort Estimations in the FSSM 137 8.1 Software Analysis – Size Determination and Effort Estimation, Static Structure, and Dynamic Characteristics in the FSSM 137 8.2 Software Size and Effort Estimation (SSEE) Description 138 8.3 Software Size and Effort Estimation (SSEE) Formulae 143 8.4 Chapter Summary 150 Exercises 152 9 Software Performance Quality Indicators for Static Structure and Dynamic Characteristics in the FSSM 153 9.1 Software Performance Quality Indicator (SPQI) Description 153 9.2 Software Performance Quality Indicator (SPQI) Construction Information Source 164 9.3 Software Performance Quality Indicator (SPQI) Formulae 165 9.4 Examples 183 9.5 Chapter Summary 183 Exercises 187 Part Five FSSM: Summary Charts 10 Summary Charts of the FSSM 191 10.1 Summary Charts of the FSSM Constituents 191 10.2 Chapter Summary 206 Part Six FSSM: Strengths 11 Software Diagnostics Based on the Software Component’s Feature Measurements and Software Performance Quality Indicators in the FSSM 209 11.1 Basic Diagnostics About the Functional Requirements Specifications (FRS) and Software, Based on the Software Component’s Feature Measurements (SCFMs) 209 11.2 Advanced Diagnostics About the System Architecture, Functional Requirements Specifications (FRS), and Software, Based on the Software Performance Quality Indicators (SPQIs) 214 11.3 Chapter Summary 216 12 Convertibility and ISO/IEC Standards Compliance of the FSSM 217 12.1 Convertibility of the FSSM to Other Functional Size Measurement (FSM) Methodology COSMIC 217 12.2 ISO/IEC Standards Compliance of the FSSM 218 12.3 Chapter Summary 225 13 Significant Strengths of the FSSM 226 13.1 Coverage Capabilities of the FSSM in Comparison with Some Existing Software Size Measurement Methodologies 226 13.2 Advantages of the FSSM Over the Currently Available Methodologies 231 13.3 Examples 239 13.4 Chapter Summary 241 Part Seven FSSM: Usage – Example 14 Example for Using the FSSM 247 14.1 Mini-FSSM Application Software Development (ASD) Introduction 247 14.2 Functional Requirements Specifications (FRS) of the Example – ‘Mini-FSSM Application Software Development’ 248 14.3 Software Component’s Feature Point (SCFP) Counting Explanation for the Example Mini-FSSM ASD 260 14.4 Software Component’s Feature Point (SCFP) Counting and Software Component’s Feature Point Count (SCFPC) Formation Table for the Example Mini-FSSM ASD 289 14.5 FSSM Results Tables for the Software Example Mini-FSSM Application Software Development 289 14.6 Graphical Representation of the Final Output Results for the Example Mini-FSSM 305 14.7 Chapter Summary 306 Part Eight Concluding Information 15 Effort Estimate for the Usage of the FSSM 313 15.1 Software Component’s Feature Point (SCFP) Counting, Analysis, and Report Preparation Effort Estimate for the Usage of the FSSM 313 15.2 Chapter Summary 315 16 Known Limitations, Improvement Scope, and Conclusion 316 16.1 Known Limitations of the FSSM 316 16.2 Improvement Possibilities in the FSSM 316 16.3 Conclusion 317 16.4 Chapter Summary 318 Part Nine Glossary 17 Glossary 321 17.1 Terms and Their Significance 321 Part Ten List of Figures and Answers to Exercises 18 List of Figures 393 19 Answers to Exercises 395 19.1 Chapter 1 Exercises 395 19.2 Chapter 2 Exercises 395 19.3 Chapter 3 Exercises 395 19.4 Chapter 4 Exercises 396 19.5 Chapter 5 Exercises 396 19.6 Chapter 6 Exercises 396 19.7 Chapter 7 Exercises 396 19.8 Chapter 8 Exercises 396 19.9 Chapter 9 Exercises 396 References 397 Index 399

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Book SynopsisADVANCES IN ENERGY STORAGE An accessible reference describing the newest advancements in energy storage technologies Advances in Energy Storage: Latest Developments from R&D to the Market is a comprehensive exploration of a wide range of energy storage technologies that use the fundamental energy conversion method. The distinguished contributors discuss the foundational principles, common materials, construction, device operation, and system level performance of the technology, as well as real-world applications. The book also includes examinations of the industry standards that apply to energy storage technologies and the commercial status of various kinds of energy storage. The book has been written by accomplished leaders in the field and address electrochemical, chemical, thermal, mechanical, and superconducting magnetic energy storage. They offer insightful treatments of relevant policy instruments and posit likely future advancements that will suppTable of ContentsList of Contributors xxi 1 Energy Storage Solutions for Future Energy Systems 1Andreas Hauer 1.1 The Role of Energy Storage 1 1.2 The Definition of Energy Storage 1 1.3 Technologies for Energy Storage 5 1.4 Applications for Energy Storage 11 Part I Electrochemical, Electrical, and Super Magnetic Energy Storages 15 2 An Introduction to Electrochemistry in Modern Power Sources 17Frank C. Walsh, Andrew Cruden, and Peter J. Hall 2.1 Introduction 17 2.2 Electrode Reactions 17 2.3 Electrochemical Cells 18 2.4 The Case for Electrochemical Power Sources 19 2.5 The Thermodynamics of Electrochemical Cells 20 2.6 The Actual Cell Voltage: Thermodynamic, Electrode Kinetic, and Ohmic Losses 20 2.7 Faraday’s Laws and Charge Capacity 22 2.8 The Performance of Cells: Charge Capacity and Specific Energy Capability 23 2.9 Types of Electrochemical Device for Energy Conversion 23 3 Standalone Batteries for Power Backup and Energy Storage 31Declan Bryans, Martin R Jiminez, Jennifer M Maxwell, Jon M Mitxelena, David Kerr, and Léonard E A Berlouis 3.1 Introduction 31 3.2 Standalone Battery Technologies 31 3.3 Comparisons 54 3.4 Conclusions 54 4 Environmental Aspects and Recycling of Battery Materials 61Guangjin Zhao 4.1 Introduction 61 4.2 Classical Batteries 63 4.3 Summary 64 4.4 Future Perspectives 64 4.5 Future Developments 68 5 Supercapacitors for Short-term, High Power Energy Storage 71Lingbin Kong, Maocheng Liu, Jianyun Cao, Rutao Wang, Weibin Zhang, Kun Yan, Xiaohong Li, and Frank C. Walsh 5.1 Introduction 71 5.2 Electrode Materials 73 5.3 Supercapacitor Devices 80 5.4 Conclusions 88 5.5 Outlook 89 6 Overview of Superconducting Magnetic Energy Storage Technology 99Jing Shi, Xiao Zhou, Yang Liu, Li Ren, Yuejin Tang, and Shijie Chen 6.1 Introduction 99 6.2 The Principle of SMES 99 6.3 Development Status of SMES 102 6.4 Development Trend of SMES 104 6.5 Research Topics for Developing SMES 107 6.6 Conclusions 109 7 Key Technologies of Superconducting Magnets for SMES 113Ying Xu, Li Ren, Jing Shi, and Yuejin Tang 7.1 Introduction 113 7.2 The Development of SMES Magnets 116 7.3 Considerations in the Design of SMES Magnets 119 7.4 Current Leads of SMES Magnets 124 7.5 Quench Protection for SMES Magnets 128 7.6 Summary 132 8 Testing Technologies for Developing SMES 135Jing Shi, Yuxiang Liao, Lihui Zhang, Ying Xu, Li Ren, Jingdong Li, and Yuejin Tang 8.1 Introduction 135 8.2 HTS Tape Property Test Method 135 8.3 Magnet Coils Experimental Methods 138 8.4 SMES Test 140 8.5 Conclusions 147 9 Superconducting Wires and Tapes for SMES 149Yuejin Tang, Ying Xu, Sinian Yan, Feng Feng, and Guo Yan 9.1 Introduction 149 9.2 A Brief Explanation of Superconductivity 150 9.3 Wires Made from LTc Superconductors 157 9.4 Wires or Tapes Made from HTc Superconductors 158 9.5 Discussion 162 10 Cryogenic Technology 165Li Ren, Ying Xu, and Yuejin Tang 10.1 Introduction 165 10.2 Cryogens 166 10.3 Cryo-cooler 170 10.4 Cryogenic System 173 10.5 Vacuum Technology 176 10.6 An Evaluation Method for Conduction-cooled SMES Cryogenic Cooling Systems 178 10.7 Case Study 181 11 Control Strategies for Different Application Modes of SMES 187Jiakun Fang, Wei Yao, Jinyu Wen, and Shijie Cheng 11.1 Overview of the Control Strategies for SMES Applications 187 11.2 Robust Control for SMES in Coordination with Wind Generators 188 11.3 Anti-windup Compensation for SMES-Based Power System Damping Controller 196 11.4 Monitoring and Control Unit of SMES 204 11.5 Conclusion 208 Part II Mechanical Energy Storage and Pumped Hydro Energy Storage 211 12 Overview of Pumped Hydro Resource 213Pål-Tore Storli 12.1 Pumped Hydro Storage Basic Concepts 213 12.2 Historic Perspective 226 12.3 Worldwide Installed Base 231 12.4 The Future for PHS 231 13 Pumped Storage Machines – Motor Generators 239Stefanie Kemmer and Thomas Hildinger 13.1 Synchronous Machine Fixed Speed 240 13.2 Doubly fed Induction Machine Adjustable Speed (DFIM) 247 13.3 Synchronous Machine Adjustable Speed (FFIM) 252 14 Pumped Storage Machines – Ternary Units 257Manfred Sallaberger and Thomas Gaal 14.1 Ternary Units 257 15 Hydro-Mechanical Equipment 273Claudia Pollak-Reibenwein 15.1 Steel-lined Pressure Conduits 273 15.2 Typical Control and Shut-Off Devices for Pumped Storage Plants 284 16 Pumped Storage Machines - Hydraulic Short-circuit Operation 289Thomas Gaal and Manfred Sallaberger 16.1 Hydraulic Short-circuit Operation 289 Part III Mechanical Energy Storage, Compressed Air Energy Storage, and Flywheels 303 17 Compressed Air Energy Storage: Are the Market and Technical Knowledge Ready? 305Pierre Bérest, Benoît Brouard, Louis Londe, and Arnaud Réveillère 17.1 Introduction 305 17.2 Historical Developments 307 17.3 Challenges Raised by Air Storage in Salt Caverns 308 17.4 (Selected) Recent Projects 314 17.5 Business Case 316 17.6 Conclusion 320 18 The Geology, Historical Background, and Developments in CAES 323David J. Evans 18.1 Introduction 323 18.2 Operational Modes – Diabatic, Adiabatic, Isothermal (Heat), Isochoric, and Isobaric (Pressure) Operations 333 18.3 Brief Review of the Historical Origins of CAES – How It All Began and Where It Is Now 334 18.4 Overview of Underground (Geological) Storage Options 341 18.5 Summary 376 19 Compressed Air Energy Storage in Aquifer and Depleted Gas Storage Reservoirs 391Michael J. King and George Moridis 19.1 Introduction 391 19.2 History of CAES Development 391 19.3 Power Train Requirements 393 19.4 How Does a CAES Energy Storage System Work? Matching the Storage System to CAES Power Train Requirements 394 19.5 Advantages and Disadvantages of CAES in Aquifer Structures and Depleted Gas Reservoirs 401 19.6 CAES Storage System Design Tools, Development, and Operation 403 19.7 Summary 405 20 Open Accumulator Isothermal Compressed Air Energy Storage (OA-ICAES) System 409Perry Y. Li, Eric Loth, Chao (Chris) Qin, Terrence W. Simon, and James D. Van de Ven 20.1 Introduction 409 20.2 Open Accumulator Isothermal Compressed Air Energy Storage (OA-ICAES) System Architecture 412 20.3 Liquid Piston Isothermal Compressor/Expander 413 20.4 Using Water Droplet Spray to Enhance Heat Transfer 425 20.5 Systems and Control 429 20.6 Discussion 432 20.7 Conclusions 434 Part IV Chemical Energy Storage 439 21 Hydrogen (or Syngas) Generation – Solar Thermal 441Jonathan Scheffe, Dylan McCord, and Diego Gordon 21.2 Solar Thermochemical Processes 447 22 Power-to-Liquids – Conversion of CO2 and Renewable H2 to Methanol 489Robin J. White 22.1 Introduction 489 22.2 Methanol Synthesis 494 22.3 Catalysts for Methanol Synthesis 496 22.4 Transitioning to Sustainable Methanol Production 500 22.5 Elaboration of a Methanol Economy 505 22.6 Conclusion and Summary 512 23 Hydrogenation Energy Recovery – Small Molecule Liquid Organic Hydrogen Carriers and Catalytic Dehydrogenation 521Jong-Hoo Choi, Dominic van der Waals, Thomas Zell, Robert Langer, and Martin H.G. Prechtl 23.1 Introduction 521 23.2 Methanol (CH3OH) 525 23.3 Formaldehyde/Methanediol (CH2O/CH2OHOH) 535 23.4 Formic Acid (HCO2H) 537 23.5 Other Alcohols, Diols, and Amino Alcohols 544 23.6 Summary and Outlook 550 24 Hydrogen Energy Recovery – H2-Based Fuel Cells 559Nada Zamel and Ulf Groos 24.1 Introduction 559 24.2 Polymer Electrolyte Membrane Fuel Cells 561 24.3 Topics of Research 569 24.4 Characterization Techniques 577 24.5 Conclusions 582 Part V Thermal Energy Storage 589 25 Thermal Energy Storage – An Introduction 591Andreas Hauer and Eberhard Laevemann 25.1 Introduction 591 25.2 Characteristic Parameters of Thermal Energy Storage 592 25.3 The Physical Storage Principle – Sensible, Latent, and Thermochemical 596 25.4 Design of a Thermal Energy Storage and Integration into an Energy System 600 25.5 Thermal Energy Storage Classification 602 25.6 Conclusions 604 26 New Phase Change Materials for Latent Heat Storage 607Elena Palomo del Barrio and Fouzia Achchaq 26.1 Introduction 607 26.2 Fundamentals, Materials, Groups, and Properties 608 26.3 Currently Used and Emerging Phase Change Materials 614 26.4 Approaches to Improve PCMs’ Properties 621 26.5 Commercial Status 627 26.6 Future Development Directions 627 27 Sorption Material Developments for TES Applications 631Alenka Ristić 27.1 Introduction 631 27.2 Sorption Materials 635 27.3 Future Developments 647 28 Vacuum Super Insulated Thermal Storage Systems for Buildings and Industrial Applications 655Thomas Beikircher and Matthias Rottmann 28.1 Introduction 655 28.2 VSI with Expanded Perlite for Highly Efficient and Economical Thermal Storages 658 28.3 Storage Media for Medium and High Temperatures 669 28.4 VSI and VSI Storages in Industrial Applications 671 28.5 Conclusions 672 29 Heat Transfer Enhancement for Latent Heat Storage Components 675Jaume Gasia, Laia Miró, Alvaro de Gracia, and Luisa F. Cabeza 29.1 Introduction 675 29.2 Heat Transfer Enhancement Techniques 676 29.3 Technology Development and Commercial Status 690 30 Reactor Design for Thermochemical Energy Storage Systems 695Wim Van Helden 30.1 Requirements for TCM Reactors 695 30.2 Charging and Discharging Processes in TCM Reactors 695 30.3 Types of Reactors and Examples of Design Solutions 699 30.4 Conclusions and Outlook 702 31 Phase Change Materials in Buildings – State of the Art 705Thomas Haussmann, Tabea Obergfell, and Stefan Gschwander 31.1 Introduction 705 31.2 Materials 707 31.3 Example of Building Integration of PCM 710 31.4 Planning Boundary Conditions 722 31.5 Long Term Experience 725 32 Industrial Applications of Thermal Energy Storage Systems 729Viktoria Martin and Ningwei Justin Chiu 32.1 Why Thermal Energy Storage in Industry? 729 32.2 Integration of TES in Industrial Scale Applications 734 32.3 Mobile TES in Innovative Energy Distribution 742 32.4 Concluding Remarks 744 33 Economy of Thermal Energy Storage Systems in Different Applications 749Christoph Rathgeber, Eberhard Lävemann, and Andreas Hauer 33.1 Introduction 749 33.2 Methods to Evaluate Thermal Energy Storage Economics 749 33.3 Comparison of Acceptable and Realized Storage Capacity Costs in Different TES Applications 752 33.4 Discussion on the Major Influencing Factors on the Economics of Thermal Energy Storage 757 33.5 Conclusions 758 Part VI Energy Storage Concepts, Regulations, and Markets 761 34 Energy Storage Can Stop Global Warming 763Halime Ö. Paksoy 34.1 Introduction 763 34.2 Energy Storage Technologies 765 34.3 Energy Storage Systems 766 34.4 The Potentials of Energy Storage 767 34.5 Policy Frameworks 771 34.6 Cross-cutting Aspects 772 34.7 Conclusions 773 35 Energy Storage Participation in Electricity Markets 775Tom Brijs, Andreas Belderbos, Kris Kessels, Daan Six, Ronnie Belmans, and Frederik Geth 35.1 Introduction 775 35.2 Classification of Energy Storage Options 777 35.3 Techno-economic Energy Storage Characteristics 782 35.4 Energy Storage Applications 784 35.5 Interaction Market Opportunities and Technical Characteristics –Illustrative Case Studies 788 35.6 Conclusions 792 36 Public Perceptions and Acceptance of Energy Storage Technologies 795Per Alex Soerensen 36.1 Introduction 795 36.2 Why Resistance? 795 36.3 Who Will Resist? 796 36.4 Cases 796 36.5 Drivers for Positive Public Perceptions and Acceptance 798 36.6 Is There a Manual for Citizen Involvement? 800 36.7 Perception of Acceptance of Energy Storage Technologies 801 37 Business Case for Energy Storage in Japan 805Masaya Okumaya 37.1 Energy Consumption in Japan 805 37.2 Electricity Situation 806 37.3 Climate Condition and Cooling/heating Load 807 37.4 Situation of Thermal Energy Storage (TES) Spread 808 37.5 Variation of TES 809 37.6 Water Storage 810 37.7 Ice Storage 811 38 Energy Storage in the Electricity Market: Business Models and Regulatory Framework in Germany 817Helena Teschner 38.1 Introduction 818 38.2 Business Models in Germany 819 38.3 Legal and Regulatory Framework – Opportunities and Barriers 829 38.4 Conclusion and Outlook 835 39 Integration of Renewable Energy by Distributed Energy Storages 839Christian Doetsch and Anna Grevé 39.1 Introduction 839 39.2 Usage of Variable Renewable Energies and Induced Problems 839 39.3 Energy Balancing Technologies and Options 843 39.4 Applications for Electric Energy Storages (Adapted from [4]) 845 39.5 Business Cases for Electric Energy Storages 847 39.6 Distributed Storage Concepts 848 39.7 Summary 849 40 Thermal Storages and Power to Heat 851Per Alex Soerensen 40.1 Introduction 851 40.2 Why Power to Heat? 851 40.3 Technologies for Power to Heat 853 40.4 Examples of Power to Heat Concepts 865 40.5 The Future. Smart Energy Systems 868 Index 871

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Book SynopsisA concise, in-depth introduction to active disturbance rejection control theory for nonlinear systems, with numerical simulations and clearly worked out equations Provides the fundamental, theoretical foundation for applications of active disturbance rejection control Features numerical simulations and clearly worked out equations Highlights the advantages of active disturbance rejection control, including small overshooting, fast convergence, and energy savings Table of ContentsPreface ix 1 Introduction 1 1.1 Problem Statement 1 1.2 Overview of Engineering Applications 6 1.3 Preliminaries 9 1.3.1 Canonical Form of ADRC 9 1.3.2 Stability for Nonlinear Systems 18 1.3.3 Stability of Linear Systems 24 1.3.4 Finite-Time Stability of Continuous System 27 1.3.5 Stability of Discontinuous Systems 32 1.3.6 Proof of Theorem 1.3.11 34 1.4 Remarks and Bibliographical Notes 50 2 The Tracking Differentiator (TD) 53 2.1 Linear Tracking Differentiator 55 2.2 Nonlinear Tracking Differentiator 59 2.2.1 Second-Order Nonlinear Tracking Differentiator 60 2.2.2 High-Order Nonlinear Tracking Differentiator 64 2.3 Finite-Time Stable System-Based Tracking Differentiator 69 2.3.1 Convergence of Finite-Time Stable System-Based TD 70 2.3.2 A Second-Order Finite-Time Stable Tracking Differentiator 75 2.4 Illustrative Examples and Applications 77 2.4.1 Comparison of Three Differentiators 77 2.4.2 Applications to Frequency Online Estimation 81 2.4.3 Application to the Boundary Stabilization of Wave Equation 85 2.5 Summary and Open Problems 88 2.6 Remarks and Bibliographical Notes 89 3 Extended State Observer 93 3.1 Linear Extended State Observer for SISO Systems 94 3.2 Nonlinear Extended State Observer for SISO Systems 100 3.2.1 Nonlinear ESO for SISO Systems 101 3.2.2 Some Special ESO 109 3.3 The ESO for SISO Systems with Time-Varying Gain 119 3.4 The ESO for MIMO Systems with Uncertainty 133 3.4.1 ESO for Systems with Total Disturbance 133 3.4.2 ESO for Systems with External Disturbance Only 141 3.4.3 Examples and Numerical Simulations 144 3.5 Summary and Open Problems 150 3.6 Remarks and Bibliographical Notes 153 4 The Active Disturbance Rejection Control 155 4.1 Linear ADRC for SISO Systems 157 4.1.1 Global Convergence of Linear ADRC for SISO Systems 157 4.1.2 Global Convergence for Systems with External Disturbance Only 167 4.1.3 Semi-Global Convergence of LADRC 176 4.1.4 Numerical Simulations 183 4.2 Nonlinear ADRC for SISO Systems 187 4.2.1 Global ADRC for SISO Systems with Total Disturbance 187 4.2.2 Global ADRC for SISO System with External Disturbance Only 195 4.2.3 Semi-global ADRC for SISO System with Vast Uncertainty 203 4.2.4 Examples and Numerical Simulations 204 4.3 ADRC with Time-Varying Tuning Parameter 206 4.4 Nonlinear ADRC for MIMO Systems with Vast Uncertainty 228 4.4.1 Semi-Global ADRC for MIMO Systems with Uncertainty 231 4.4.2 Global ADRC for MIMO Systems with Uncertainty 238 4.4.3 Global ADRC for MIMO Systems with External Disturbance Only 245 4.4.4 Numerical Simulations 250 4.5 IMP Versus ADRC 252 4.6 HGC and SMC Versus ADRC 263 4.7 Applications to PMSMs 267 4.8 Application to Wave Equation with Uncertainty 270 4.8.1 Control Design 271 4.8.2 Proof of Theorem 4.8.1 279 4.9 Summary and Open Problems 287 4.10 Remarks and Bibliographical Notes 289 5 ADRC for Lower Triangular Nonlinear Systems 291 5.1 ESO for Lower Triangular Systems 291 5.1.1 Constant High-Gain ESO 292 5.1.2 Time-Varying Gain ESO 301 5.1.3 Numerical Simulation 306 5.2 Stabilization of Lower Triangular Systems by ADRC 312 5.2.1 ADRC with Constant Gain ESO 313 5.2.2 ADRC with Time-Varying Gain ESO 327 5.3 Numerical Simulations 331 5.4 Summary and Open Problems 336 5.5 Remarks and Bibliographical Notes 338 References 341 Index 349

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Book SynopsisPHOTOVOLTAIC MANUFACTURING This book covers the state-of-the-art and the fundamentals of silicon wafer solar cells manufacturing, written by world-class researchers and experts in the field. High quality and economic photovoltaic manufacturing is central to realizing reliable photovoltaic power supplies at reasonable cost. While photovoltaic silicon wafer manufacturing is at a mature, industrial and mass production stage, knowing and applying the fundamentals in solar manufacturing is essential to anyone working in this field. This is the first book on photovoltaic wet processing for silicon wafers, both mono- and multi-crystalline. The comprehensive book provides information for process, equipment, and device engineers and researchers in the solar manufacturing field. The authors of the chapters are world-class researchers and experts in their field of endeavor. The fundamentals of wet processing chemistry are introduced, covering etching, texturing, cleaning an

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Book SynopsisA synergy of techniques on hybrid intelligence for real-life image analysis Hybrid Intelligence for Image Analysis and Understanding brings together research on the latest results and progress in the development of hybrid intelligent techniques for faithful image analysis and understanding.Table of ContentsEditor Biographies xvii List of Contributors xxi Foreword xxvii Preface xxxi About the Companion website xxxv 1 Multilevel Image Segmentation UsingModified Genetic Algorithm (MfGA)-based Fuzzy C-Means 1Sourav De, Sunanda Das, Siddhartha Bhattacharyya, and Paramartha Dutta 1.1 Introduction 1 1.2 Fuzzy C-Means Algorithm 5 1.3 Modified Genetic Algorithms 6 1.4 Quality Evaluation Metrics for Image Segmentation 8 1.4.1 Correlation Coefficient 8 1.4.2 Empirical Measure Q(I) 8 1.5 MfGA-Based FCM Algorithm 9 1.6 Experimental Results and Discussion 11 1.7 Conclusion 22 References 22 2 Character Recognition Using Entropy-Based Fuzzy C-Means Clustering 25B. Kondalarao, S. Sahoo, and D.K. Pratihar 2.1 Introduction 25 2.2 Tools and Techniques Used 27 2.2.1 Fuzzy Clustering Algorithms 27 2.2.1.1 Fuzzy C-means Algorithm 28 2.2.1.2 Entropy-based Fuzzy Clustering 29 2.2.1.3 Entropy-based Fuzzy C-Means Algorithm 29 2.2.2 Sammon’s Nonlinear Mapping 30 2.3 Methodology 31 2.3.1 Data Collection 31 2.3.2 Preprocessing 31 2.3.3 Feature Extraction 32 2.3.4 Classification and Recognition 34 2.4 Results and Discussion 34 2.5 Conclusion and Future Scope ofWork 38 References 39 Appendix 41 3 A Two-Stage Approach to Handwritten Indic Script Identification 47Pawan Kumar Singh, Supratim Das, Ram Sarkar, andMita Nasipuri 3.1 Introduction 47 3.2 Review of RelatedWork 48 3.3 Properties of Scripts Used in the PresentWork 51 3.4 ProposedWork 52 3.4.1 DiscreteWavelet Transform 53 3.4.1.1 HaarWavelet Transform 55 3.4.2 Radon Transform (RT) 57 3.5 Experimental Results and Discussion 63 3.5.1 Evaluation of the Present Technique 65 3.5.1.1 Statistical Significance Tests 66 3.5.2 Statistical Performance Analysis of SVM Classifier 68 3.5.3 Comparison with Other RelatedWorks 71 3.5.4 Error Analysis 73 3.6 Conclusion 74 Acknowledgments 75 References 75 4 Feature Extraction and Segmentation Techniques in a Static Hand Gesture Recognition System 79Subhamoy Chatterjee, Piyush Bhandari, and Mahesh Kumar Kolekar 4.1 Introduction 79 4.2 Segmentation Techniques 81 4.2.1 Otsu Method for Gesture Segmentation 81 4.2.2 Color Space–Based Models for Hand Gesture Segmentation 82 4.2.2.1 RGB Color Space–Based Segmentation 82 4.2.2.2 HSI Color Space–Based Segmentation 83 4.2.2.3 YCbCr Color Space–Based Segmentation 83 4.2.2.4 YIQ Color Space–Based Segmentation 83 4.2.3 Robust Skin Color Region Detection Using K-Means Clustering and Mahalanobish Distance 84 4.2.3.1 Rotation Normalization 85 4.2.3.2 Illumination Normalization 85 4.2.3.3 Morphological Filtering 85 4.3 Feature Extraction Techniques 86 4.3.1 Theory of Moment Features 86 4.3.2 Contour-Based Features 88 4.4 State of the Art of Static Hand Gesture Recognition Techniques 89 4.4.1 Zoning Methods 90 4.4.2 F-Ratio-BasedWeighted Feature Extraction 90 4.4.3 Feature Fusion Techniques 91 4.5 Results and Discussion 92 4.5.1 Segmentation Result 93 4.5.2 Feature Extraction Result 94 4.6 Conclusion 97 4.6.1 FutureWork 99 Acknowledgment 99 References 99 5 SVM Combination for an Enhanced Prediction ofWriters’ Soft Biometrics 103Nesrine Bouadjenek, Hassiba Nemmour, and Youcef Chibani 5.1 Introduction 103 5.2 Soft Biometrics and Handwriting Over Time 104 5.3 Soft Biometrics Prediction System 106 5.3.1 Feature Extraction 107 5.3.1.1 Local Binary Patterns 107 5.3.1.2 Histogram of Oriented Gradients 108 5.3.1.3 Gradient Local Binary Patterns 108 5.3.2 Classification 109 5.3.3 Fuzzy Integrals–Based Combination Classifier 111 5.3.3.1 g�� Fuzzy Measure 111 5.3.3.2 Sugeno’s Fuzzy Integral 113 5.3.3.3 Fuzzy Min-Max 113 5.4 Experimental Evaluation 113 5.4.1 Data Sets 113 5.4.1.1 IAM Data Set 113 5.4.1.2 KHATT Data Set 114 5.4.2 Experimental Setting 114 5.4.3 Gender Prediction Results 117 5.4.4 Handedness Prediction Results 117 5.4.5 Age Prediction Results 118 5.5 Discussion and Performance Comparison 118 5.6 Conclusion 120 References 121 6 Brain-Inspired Machine Intelligence for Image Analysis: Convolutional Neural Networks 127Siddharth Srivastava and Brejesh Lall 6.1 Introduction 127 6.2 Convolutional Neural Networks 129 6.2.1 Building Blocks 130 6.2.1.1 Perceptron 134 6.2.2 Learning 135 6.2.2.1 Gradient Descent 136 6.2.2.2 Back-Propagation 136 6.2.3 Convolution 139 6.2.4 Convolutional Neural Networks:The Architecture 141 6.2.4.1 Convolution Layer 142 6.2.4.2 Pooling Layer 145 6.2.4.3 Dense or Fully Connected Layer 146 6.2.5 Considerations in Implementation of CNNs 146 6.2.6 CNN in Action 147 6.2.7 Tools for Convolutional Neural Networks 148 6.2.8 CNN Coding Examples 148 6.2.8.1 MatConvNet 148 6.2.8.2 Visualizing a CNN 149 6.2.8.3 Image Category Classification Using Deep Learning 153 6.3 Toward Understanding the Brain, CNNs, and Images 157 6.3.1 Applications 157 6.3.2 Case Studies 158 6.4 Conclusion 159 References 159 7 Human Behavioral Analysis Using Evolutionary Algorithms and Deep Learning 165Earnest Paul Ijjina and Chalavadi Krishna Mohan 7.1 Introduction 165 7.2 Human Action Recognition Using Evolutionary Algorithms and Deep Learning 167 7.2.1 Evolutionary Algorithms for Search Optimization 168 7.2.2 Action Bank Representation for Action Recognition 168 7.2.3 Deep Convolutional Neural Network for Human Action Recognition 169 7.2.4 CNN Classifier Optimized Using Evolutionary Algorithms 170 7.3 Experimental Study 170 7.3.1 Evaluation on the UCF50 Data Set 170 7.3.2 Evaluation on the KTH Video Data Set 172 7.3.3 Analysis and Discussion 176 7.3.4 Experimental Setup and Parameter Optimization 177 7.3.5 Computational Complexity 182 7.4 Conclusions and FutureWork 183 References 183 8 Feature-Based Robust Description andMonocular Detection: An Application to Vehicle Tracking 187Ramazan Yíldíz and Tankut Acarman 8.1 Introduction 187 8.2 Extraction of Local Features by SIFT and SURF 188 8.3 Global Features: Real-Time Detection and Vehicle Tracking 190 8.4 Vehicle Detection and Validation 194 8.4.1 X-Analysis 194 8.4.2 Horizontal Prominent Line Frequency Analysis 195 8.4.3 Detection History 196 8.5 Experimental Study 197 8.5.1 Local Features Assessment 197 8.5.2 Global Features Assessment 197 8.5.3 Local versus Global Features Assessment 201 8.6 Conclusions 201 References 202 9 A GIS Anchored Technique for Social Utility Hotspot Detection 205Anirban Chakraborty, J.K.Mandal, Arnab Patra, and JayatraMajumdar 9.1 Introduction 205 9.2 The Technique 207 9.3 Case Study 209 9.4 Implementation and Results 221 9.5 Analysis and Comparisons 224 9.6 Conclusions 229 Acknowledgments 229 References 230 10 Hyperspectral Data Processing: Spectral Unmixing, Classification, and Target Identification 233Vaibhav Lodhi, Debashish Chakravarty, and PabitraMitra 10.1 Introduction 233 10.2 Background and Hyperspectral Imaging System 234 10.3 Overview of Hyperspectral Image Processing 236 10.3.1 Image Acquisition 237 10.3.2 Calibration 237 10.3.3 Spatial and Spectral preprocessing 238 10.3.4 Dimension Reduction 239 10.3.4.1 Transformation-Based Approaches 239 10.3.4.2 Selection-Based Approaches 239 10.3.5 postprocessing 240 10.4 Spectral Unmixing 240 10.4.1 Unmixing Processing Chain 240 10.4.2 Mixing Model 241 10.4.2.1 Linear Mixing Model (LMM) 242 10.4.2.2 Nonlinear Mixing Model 242 10.4.3 Geometrical-Based Approaches to Linear Spectral Unmixing 243 10.4.3.1 Pure Pixel-Based Techniques 243 10.4.3.2 Minimum Volume-Based Techniques 244 10.4.4 Statistics-Based Approaches 244 10.4.5 Sparse Regression-Based Approach 245 10.4.5.1 Moore–Penrose Pseudoinverse (MPP) 245 10.4.5.2 Orthogonal Matching Pursuit (OMP) 246 10.4.5.3 Iterative Spectral Mixture Analysis (ISMA) 246 10.4.6 Hybrid Techniques 246 10.5 Classification 247 10.5.1 Feature Mining 247 10.5.1.1 Feature Selection (FS) 248 10.5.1.2 Feature Extraction 248 10.5.2 Supervised Classification 248 10.5.2.1 Minimum Distance Classifier 249 10.5.2.2 Maximum Likelihood Classifier (MLC) 250 10.5.2.3 Support Vector Machines (SVMs) 250 10.5.3 Hybrid Techniques 250 10.6 Target Detection 251 10.6.1 Anomaly Detection 251 10.6.1.1 RX Anomaly Detection 252 10.6.1.2 Subspace-Based Anomaly Detection 253 10.6.2 Signature-Based Target Detection 253 10.6.2.1 Euclidean distance 254 10.6.2.2 Spectral Angle Mapper (SAM) 254 10.6.2.3 Spectral Matched Vilter (SMF) 254 10.6.2.4 Matched Subspace Detector (MSD) 255 10.6.3 Hybrid Techniques 255 10.7 Conclusions 256 References 256 11 A Hybrid Approach for Band Selection of Hyperspectral Images 263Aditi Roy Chowdhury, Joydev Hazra, and Paramartha Dutta 11.1 Introduction 263 11.2 Relevant Concept Revisit 266 11.2.1 Feature Extraction 266 11.2.2 Feature Selection Using 2D PCA 266 11.2.3 Immune Clonal System 267 11.2.4 Fuzzy KNN 268 11.3 Proposed Algorithm 271 11.4 Experiment and Result 271 11.4.1 Description of the Data Set 272 11.4.2 Experimental Details 274 11.4.3 Analysis of Results 275 11.5 Conclusion 278 References 279 12 Uncertainty-Based Clustering Algorithms for Medical Image Analysis 283Deepthi P. Hudedagaddi and B.K. Tripathy 12.1 Introduction 283 12.2 Uncertainty-Based Clustering Algorithms 283 12.2.1 Fuzzy C-Means 284 12.2.2 Rough Fuzzy C-Means 285 12.2.3 Intuitionistic Fuzzy C-Means 285 12.2.4 Rough Intuitionistic Fuzzy C-Means 286 12.3 Image Processing 286 12.4 Medical Image Analysis with Uncertainty-Based Clustering Algorithms 287 12.4.1 FCM with Spatial Information for Image Segmentation 287 12.4.2 Fast and Robust FCM Incorporating Local Information for Image Segmentation 290 12.4.3 Image Segmentation Using Spatial IFCM 291 12.4.3.1 Applications of Spatial FCM and Spatial IFCM on Leukemia Images 292 12.5 Conclusions 293 References 293 13 An Optimized Breast Cancer Diagnosis SystemUsing a Cuckoo Search Algorithm and Support Vector Machine Classifier 297Manoharan Prabukumar, Loganathan Agilandeeswari, and Arun Kumar Sangaiah 13.1 Introduction 297 13.2 Technical Background 301 13.2.1 Morphological Segmentation 301 13.2.2 Cuckoo Search Optimization Algorithm 302 13.2.3 Support Vector Machines 303 13.3 Proposed Breast Cancer Diagnosis System 303 13.3.1 Preprocessing of Breast Cancer Image 303 13.3.2 Feature Extraction 304 13.3.2.1 Geometric Features 304 13.3.2.2 Texture Features 305 13.3.2.3 Statistical Features 306 13.3.3 Features Selection 306 13.3.4 Features Classification 307 13.4 Results and Discussions 307 13.5 Conclusion 310 13.6 FutureWork 310 References 310 14 Analysis of Hand Vein Images Using Hybrid Techniques 315R. Sudhakar, S. Bharathi, and V. Gurunathan 14.1 Introduction 315 14.2 Analysis of Vein Images in the Spatial Domain 318 14.2.1 Preprocessing 318 14.2.2 Feature Extraction 319 14.2.3 Feature-Level Fusion 320 14.2.4 Score Level Fusion 320 14.2.5 Results and Discussion 322 14.2.5.1 Evaluation Metrics 323 14.3 Analysis of Vein Images in the Frequency Domain 326 14.3.1 Preprocessing 326 14.3.2 Feature Extraction 326 14.3.3 Feature-Level Fusion 330 14.3.4 Support Vector Machine Classifier 331 14.3.5 Results and Discussion 331 14.4 Comparative Analysis of Spatial and Frequency Domain Systems 332 14.5 Conclusion 335 References 335 15 Identification of Abnormal Masses in Digital Mammogram Using Statistical Decision Making 339Indra Kanta Maitra and Samir Kumar Bandyopadhyay 15.1 Introduction 339 15.1.1 Breast Cancer 339 15.1.2 Computer-Aided Detection/Diagnosis (CAD) 340 15.1.3 Segmentation 340 15.2 PreviousWorks 341 15.3 Proposed Method 343 15.3.1 Preparation 343 15.3.2 Preprocessing 345 15.3.2.1 Image Enhancement and Edge Detection 346 15.3.2.2 Isolation and Suppression of Pectoral Muscle 348 15.3.2.3 Breast Contour Detection 351 15.3.2.4 Anatomical Segmentation 353 15.3.3 Identification of Abnormal Region(s) 354 15.3.3.1 Coloring of Regions 354 15.3.3.2 Statistical Decision Making 355 15.4 Experimental Result 358 15.4.1 Case Study with Normal Mammogram 358 15.4.2 Case Study with Abnormalities Embedded in Fatty Tissues 358 15.4.3 Case Study with Abnormalities Embedded in Fatty-Fibro-Glandular Tissues 359 15.4.4 Case Study with Abnormalities Embedded in Dense-Fibro-Glandular Tissues 359 15.5 Result Evaluation 360 15.5.1 Statistical Analysis 361 15.5.2 ROC Analysis 361 15.5.3 Accuracy Estimation 365 15.6 Comparative Analysis 366 15.7 Conclusion 366 Acknowledgments 366 References 367 16 Automatic Detection of Coronary Artery Stenosis Using Bayesian Classification and Gaussian Filters Based on Differential Evolution 369Ivan Cruz-Aceves, Fernando Cervantes-Sanchez, and Arturo Hernandez-Aguirre 16.1 Introduction 369 16.2 Background 370 16.2.1 Gaussian Matched Filters 371 16.2.2 Differential Evolution 371 16.2.2.1 Example: Global Optimization of the Ackley Function 373 16.2.3 Bayesian Classification 375 16.2.3.1 Example: Classification Problem 375 16.3 Proposed Method 377 16.3.1 Optimal Parameter Selection of GMF Using Differential Evolution 377 16.3.2 Thresholding of the Gaussian Filter Response 378 16.3.3 Stenosis Detection Using Second-Order Derivatives 378 16.3.4 Stenosis Detection Using Bayesian Classification 379 16.4 Computational Experiments 381 16.4.1 Results of Vessel Detection 382 16.4.2 Results of Vessel Segmentation 382 16.4.3 Evaluation of Detection of Coronary Artery Stenosis 384 16.5 Concluding Remarks 386 Acknowledgment 388 References 388 17 Evaluating the Efficacy of Multi-resolution Texture Features for Prediction of Breast Density UsingMammographic Images 391Kriti, Harleen Kaur, and Jitendra Virmani 17.1 Introduction 391 17.1.1 Comparison of Related Methods with the Proposed Method 397 17.2 Materials and Methods 398 17.2.1 Description of Database 398 17.2.2 ROI Extraction Protocol 398 17.2.3 Workflow for CAD System Design 398 17.2.3.1 Feature Extraction 400 17.2.3.2 Classification 407 17.3 Results 410 17.3.1 Results Based on Classification Performance of the Classifiers (Classification Accuracy and Sensitivity) for Each Class 411 17.3.1.1 Experiment I: To Determine the Performance of Different FDVs Using SVM Classifier 411 17.3.1.2 Experiment II: To Determine the Performance of Different FDVs Using SSVM Classifier 412 17.3.2 Results Based on Computational Efficiency of Classifiers for Predicting 161 Instances of Testing Dataset 412 17.4 Conclusion and Future Scope 413 References 415 Index 423

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Book SynopsisA guide to all practical aspects of building, implementing, managing, and maintaining MPC applications in industrial plants Multivariable Predictive Control: Applications in Industry provides engineers with a thorough understanding of all practical aspects of multivariate predictive control (MPC) applications, as well as expert guidance on how to derive maximum benefit from those systems. Short on theory and long on step-by-step information, it covers everything plant process engineers and control engineers need to know about building, deploying, and managing MPC applications in their companies. MPC has more than proven itself to be one the most important tools for optimising plant operations on an ongoing basis. Companies, worldwide, across a range of industries are successfully using MPC systems to optimise materials and utility consumption, reduce waste, minimise pollution, and maximise production. Unfortunately, due in part to the lack of practical reTable of ContentsFigure List xix Table List xxi Preface xxiii 1 Introduction of Model Predictive Control 1 1.1 Purpose of Process Control in Chemical Process Industries (CPI) 1 1.2 Shortcomings of Simple Regulatory PID Control 2 1.3 What Is Multivariable Model Predictive Control? 3 1.4 Why Is a Multivariable Model Predictive Optimizing Controller Necessary? 4 1.5 Relevance of Multivariable Predictive Control (MPC) in Chemical Process Industry in Today’s Business Environment 6 1.6 Position of MPC in Control Hierarchy 6 1.6.1 Regulatory PID Control Layer 6 1.6.2 Advance Regulatory Control (ARC) Layer 8 1.6.3 Multivariable Model‐Based Control 8 1.6.4 Economic Optimization Layer 8 1.6.4.1 First Layer of Optimization 8 1.6.4.2 Second Layer of Optimization 9 1.6.4.3 Third Layer of Optimization 9 1.7 Advantage of Implementing MPC 10 1.8 How Does MPC Extract Benefit? 13 1.8.1 MPC Inherent Stabilization Effect 13 1.8.2 Process Interactions 14 1.8.3 Multiple Constraints 15 1.8.4 Intangible Benefits of MPC 17 1.9 Application of MPC in Oil Refinery, Petrochemical, Fertilizer, and Chemical Plants, and Related Benefits 17 2 Theoretical Base of MPC 23 2.1 Why MPC? 23 2.2 Variables Used in MPC 25 2.2.1 Manipulated Variables (MVs) 25 2.2.2 Controlled Variables (CVs) 25 2.2.3 Disturbance Variables (DVs) 25 2.3 Features of MPC 26 2.3.1 MPC Is a Multivariable Controller 26 2.3.2 MPC Is a Model Predictive Controller 26 2.3.3 MPC Is a Constrained Controller 26 2.3.4 MPC Is an Optimizing Controller 27 2.3.5 MPC Is a Rigorous Controller 27 2.4 Brief Introduction to Model Predictive Control Techniques 27 2.4.1 Simplified Dynamic Control Strategy of MPC 28 2.4.2 Step 1: Read Process Input and Output 29 2.4.3 Step 2: Prediction of CVs 30 2.4.3.1 Building Dynamic Process Model 30 2.4.3.2 How MPC Predicts the Future 32 2.4.4 Step 3: Model Reconciliation 33 2.4.5 Step 4: Determine the Size of the Control Process 34 2.4.6 Step 5: Removal of Ill‐Conditioned Problems 34 2.4.7 Step 6: Optimum Steady‐State Targets 35 2.4.8 Step 7: Develop Detailed Plan of MV Movement 36 3 Historical Development of Different MPC Technology 43 3.1 History of MPC Technology 43 3.1.1 Pre‐Era 43 3.1.1.1 Developer 43 3.1.1.2 Motivation 44 3.1.1.3 Limitations 44 3.1.2 First Generation of MPC (1970–1980) 44 3.1.2.1 Characteristics of First‐Generation MPC Technology 44 3.1.2.2 IDCOM Algorithm and Its Features 45 3.1.2.3 DMC Algorithm and Its Features 46 3.1.3 Second‐Generation MPC (1980–1985) 46 3.1.4 Third‐Generation MPC (1985–1990) 47 3.1.4.1 Distinguishing Features of Third‐Generation MPC Algorithm 48 3.1.4.2 Distinguishing Features of the IDCOM‐M Algorithm 49 3.1.4.3 Evolution of SMOC 50 3.1.4.4 Distinctive Features of SMOC 50 3.1.5 Fourth‐Generation MPC (1990–2000) 50 3.1.5.1 Distinctive Features of Fourth‐Generation MPC 51 3.1.6 Fifth‐Generation MPC (2000–2015) 51 3.2 Points to Consider While Selecting an MPC 52 4 MPC Implementation Steps 55 4.1 Implementing a MPC Controller 55 4.1.1 Step 1: Preliminary Cost–Benefit Analysis 55 4.1.2 Step 2: Assessment of Base Control Loops 55 4.1.3 Step 3: Functional Design of Controller 56 4.1.4 Step 4: Conduct the Preliminary Plant Test (Pre‐Stepping) 57 4.1.5 Step 5: Conduct the Plant Step Test 57 4.1.6 Step 6: Identify a Process Model 57 4.1.7 Step 7: Generate Online Soft Sensors or Virtual Sensors 58 4.1.8 Step 8: Perform Offline Controller Simulation/Tuning 58 4.1.9 Step 9: Commission the Online Controller 58 4.1.10 Step 10: Online MPC Controller Tuning 59 4.1.11 Step 11: Hold Formal Operator Training 59 4.1.12 Step 12: Performance Monitoring of MPC Controller 59 4.1.13 Step 13: Maintain the MPC Controller 60 4.2 Summary of Steps Involved in MPC Projects with Vendor 60 5 Cost–Benefit Analysis of MPC before Implementation 63 5.1 Purpose of Cost–Benefit Analysis of MPC before Implementation 63 5.2 Overview of Cost–Benefit Analysis Procedure 64 5.3 Detailed Benefit Estimation Procedures 65 5.3.1 Initial Screening for Suitability of Process to Implement MPC 65 5.3.2 Process Analysis and Economics Analysis 66 5.3.3 Understand the Constraints 67 5.3.4 Identify Qualitatively Potential Area of Opportunities 67 5.3.4.1 Example 1: Air Separation Plant 68 5.3.4.2 Example 2: Distillation Columns 69 5.3.5 Collect All Relevant Plant and Economic Data (Trends, Records) 69 5.3.6 Calculate the Standard Deviation and Define the Limit 69 5.3.7 Estimate the Stabilizing Effect of MPC and Shift in the Average 70 5.3.7.1 Benefit Estimation: When the Constraint Is Known 71 5.3.7.2 Benefit Estimation: When the Constraint Is Not Well Known or Changing 72 5.3.8 Estimate Change in Key Performance Parameters Such as Yield, Throughput, and Energy Consumption 72 5.3.8.1 Example: Ethylene Oxide Reactor 72 5.3.9 Identify How This Effect Translates to Plant Profit Margin 73 5.3.10 Estimate the Economic Value of the Effect 73 5.4 Case Studies 73 5.4.1 Case Study 1 73 5.4.1.1 Benefit Estimation Procedure 73 5.4.2 Case Study 2 74 5.4.2.1 Benefit Estimation Procedure 74 6 Assessment of Regulatory Base Control Layer in Plants 77 6.1 Failure Mode of Control Loops and Their Remedies 77 6.2 Control Valve Problems 77 6.2.1 Improper Valve Sizing 78 6.2.1.1 How to Detect a Particular Control Valve Sizing Problem 78 6.2.2 Valve Stiction 79 6.2.2.1 What Is Control Valve Stiction? 79 6.2.2.2 How to Detect Control Valve Stiction Online 80 6.2.2.3 Combating Stiction 80 6.2.2.4 Techniques for Combating Stiction Online 80 6.2.3 Valve Hysteresis and Backlash 81 6.3 Sensor Problems 82 6.3.1 Noisy 82 6.3.2 Flatlining 82 6.3.3 Scale/Range 82 6.3.4 Calibration 82 6.3.5 Overfiltered 83 6.4 Controller Problems 83 6.4.1 Poor Tuning and Lack of Maintenance 83 6.4.2 Poor or Missing Feedforward Compensation 83 6.4.3 Inappropriate Control Structure 84 6.5 Process‐Related Problems 84 6.5.1 Problems of Variable Gain 84 6.5.2 Oscillations 84 6.5.2.1 Variable Valve Gain 85 6.5.2.2 Variable Process Gain 85 6.6 Human Factor 85 6.7 Control Performance Assessment/Monitoring 86 6.7.1 Available Software for Control Performance Monitoring 86 6.7.2 Basic Assessment Procedure 87 6.8 Commonly Used Control System Performance KPIs 87 6.8.1 Traditional Indices 88 6.8.1.1 Peak Overshoot Ratio (POR) 88 6.8.1.2 Decay Rate 88 6.8.1.3 Peak Time and Rise Time 88 6.8.1.4 Settling Time 88 6.8.1.5 Integral of Error Indexes 88 6.8.2 Simple Statistical Indices 88 6.8.2.1 Mean of Control Error (%) 89 6.8.2.2 Standard Deviation of Control Error (%) 89 6.8.2.3 Standard Variation of Control Error (%) 89 6.8.2.4 Standard Deviation of Controller Output (%) 89 6.8.2.5 Skewness of Control Error 89 6.8.2.6 Kurtosis of Control Error 89 6.8.2.7 Ratio of Standard of Control Error and Controller Output 89 6.8.2.8 Maximum Bicoherence 90 6.8.3 Business/Operational Metrics 90 6.8.3.1 Loop Health 90 6.8.3.2 Service Factor 90 6.8.3.3 Key Performance Indicators 90 6.8.3.4 Operational Performance Efficiency Factor 90 6.8.3.5 Overall Loop Performance Index 90 6.8.3.6 Controller Output Changes in Manual 90 6.8.3.7 Mode Changes 90 6.8.3.8 Totalized Valve Reversals and Valve Travel 90 6.8.3.9 Process Model Parameters 90 6.8.4 Advanced Indices 90 6.8.4.1 Harris Index 91 6.8.4.2 Nonlinearity Index 91 6.8.4.3 Oscillation‐Detection Indices 91 6.8.4.4 Disturbance Detection Indices 92 6.8.4.5 Autocorrelation Indices 92 6.9 Tuning for PID Controllers 92 6.9.1 Complications with Tuning PID Controllers 93 6.9.2 Loop Retuning 93 6.9.3 Classical Controller Tuning Algorithms 94 6.9.3.1 Controller Tuning Methods 94 6.9.3.2 Ziegler‐Nichols Tuning Method 94 6.9.3.3 Dahlin (Lambda) Tuning Method 94 6.9.4 Manual Controller Tuning Methods in Absence of Any Software 95 6.9.4.1 Pre‐Tuning 95 6.9.4.2 Bring in Baseline Parameters 97 6.9.4.3 Some Like It Simple 97 6.9.4.4 Tuning Cascade Control 98 7 Functional Design of MPC Controllers 101 7.1 What Is Functional Design? 101 7.2 Steps in Functional Design 102 7.2.1 Step 1: Define Process Control Objectives 102 7.2.1.1 Economic Objectives 102 7.2.1.2 Operating Objectives 103 7.2.1.3 Control Objectives 104 7.2.2 Step 2: Identify Process Constraints 104 7.2.2.1 Process Limitations 104 7.2.2.2 Safety Limitations 104 7.2.2.3 Process Instrument Limitations 105 7.2.2.4 Raw Material and Utility Supply Limitation 105 7.2.2.5 Product Limitations 105 7.2.3 Step 3: Define Controller Scope 105 7.2.4 Step 4: Select the Variables 106 7.2.4.1 Economics of the Unit 106 7.2.4.2 Constraints of the Unit 107 7.2.4.3 Control of the Unit 107 7.2.4.4 Manipulated Variables (MVs) 107 7.2.4.5 Controlled Variables (CVs) 107 7.2.4.6 Disturbance Variables (DVs) 108 7.2.4.7 Practical Guidelines for Variable Selections 108 7.2.5 Step 5: Rectify Regulatory Control Issues 109 7.2.5.1 Practical Guidelines for Changing Regulatory Controller Strategy 109 7.2.6 Step 6: Explore the Scope of Inclusions of Inferential Calculations 110 7.2.7 Step 7: Evaluate Potential Optimization Opportunity 110 7.2.7.1 Practical Guidelines for Finding out Optimization Opportunities 111 7.2.8 Step 8: Define LP or QP Objective Function 111 7.2.8.1 CDU Example 112 8 Preliminary Process Test and Step Test 113 8.1 Pre‐Stepping, or Preliminary Process Test 113 8.1.1 What Is Pre‐Stepping? 113 8.1.2 Objective of Pre‐Stepping 113 8.1.3 Prerequisites of Pre‐Stepping 113 8.1.4 Pre‐Stepping 114 8.2 Step Testing 115 8.2.1 What Is a Step Test? 115 8.2.2 What Is the Purpose of a Step Test? 115 8.2.3 Details of Step Testing 116 8.2.3.1 Administrative Aspects 116 8.2.3.2 Technical Aspects 116 8.2.4 Different Step‐Testing Method 117 8.2.4.1 Manual Step Testing 117 8.2.4.2 PRBS (Pseudo Random Binary Sequence) 117 8.2.4.3 General Guidelines of PRBS Test 117 8.2.5 Difference between Normal Step Testing and PRBS Testing 118 8.2.6 Which One to Choose? 118 8.2.7 Dos and Don’ts of Step Testing 118 8.3 Development of Step‐Testing Methodology over the Years 120 9 Model Building and System Identification 123 9.1 Introduction to Model Building 123 9.2 Key Issues in Model Identifications 124 9.2.1 Identification Test 124 9.2.2 Model Structure and Parameter Estimation 125 9.2.3 Order Selection 126 9.2.4 Model Validation 127 9.3 The Basic Steps of System Identification 127 9.3.1 Step 0: Experimental Design and Execution 128 9.3.2 Step 1: Plan the Case that Needs to Be Modeled 130 9.3.2.1 Action 1 130 9.3.2.2 Action 2 130 9.3.3 Step 2: Identify Good Slices of Data 130 9.3.3.1 Looking at the Data 131 9.3.4 Step 3: Pre‐Processing of Data 131 9.3.5 Step 4: Identification of Model Curve 132 9.3.5.1 Hybrid Approach to System Identification 132 9.3.5.2 Direct Modeling Approach of System Identification 133 9.3.5.3 Subspace Identification 134 9.3.5.4 Detailed Steps of Implementations 135 9.3.6 Step 5: Select Final Model 136 9.4 Model Structures 137 9.4.1 FIR Models 138 9.4.1.1 FIR Structures 138 9.4.2 Prediction Error Models (PEM Models) 139 9.4.2.1 PEM Structures 139 9.4.3 Model for Order and Variance Reduction 140 9.4.3.1 ARX Parametric Models (Discrete Time) 140 9.4.3.2 Output Error Models (Discrete Time) 140 9.4.3.3 Laplace Domain Parametric Models 141 9.4.3.4 Final Model Form 141 9.4.4 State‐Space Models 141 9.4.5 How to Know Which Structure and Method to Use 142 9.5 Common Features of Commercial Identification Packages 142 10 Soft Sensors 145 10.1 What Is a Soft Sensor? 145 10.2 Why Soft Sensors Are Necessary 145 10.2.1 Process Monitoring and Process Fault Detection 146 10.2.2 Sensor Fault Detection and Reconstruction 146 10.2.3 Use of Soft Sensors in MPC Application 146 10.3 Types of Soft Sensors 147 10.3.1 First Principle‐Based Soft Sensors 147 10.3.1.1 Advantages 147 10.3.1.2 Disadvantages 147 10.3.2 Data‐Driven Soft Sensors 148 10.3.2.1 Advantages 148 10.3.2.2 Disadvantages 148 10.3.3 Gray Model‐Based Soft Sensors 148 10.3.3.1 Advantages 149 10.3.4 Hybrid Model‐Based Soft Sensors 149 10.3.4.1 Advantages 149 10.4 Soft Sensors Development Methodology 149 10.4.1 Data Collection and Data Inspection 149 10.4.2 Data Preprocessing and Data Conditioning 150 10.4.2.1 Outlier Detection and Replacement 151 10.4.2.2 Univariate Approach to Detect Outliers 151 10.4.2.3 Multivariate Approach to Detect Outliers (Lin 2007) 151 10.4.2.4 Handling of Missing Data 152 10.4.3 Selection of Relevant Input Output Variables 153 10.4.4 Data Alignment 153 10.4.5 Model Selection, Training, and Validation (Kadlec 2009; Lin 2007) 153 10.4.6 Analyze Process Dynamics 154 10.4.7 Deployment and Maintenance 155 10.5 Data‐Driven Methods for Soft Sensing 156 10.5.1 Principle Component Analysis 156 10.5.1.1 The Basics of PCA 156 10.5.1.2 Why Do We Need to Rotate the Data? 156 10.5.1.3 How Do We Generate Principal Components? 156 10.5.1.4 Steps to Calculating Principal Components 157 10.5.2 Partial Least Squares 157 10.5.3 Artificial Neural Networks 158 10.5.3.1 Network Architecture 159 10.5.3.2 Back Propagation Algorithm (BPA) 159 10.5.4 Neuro‐Fuzzy Systems 160 10.5.5 Support Vector Machines 161 10.5.5.1 Support Vector Regression–Based Modeling 161 10.6 Open Issues and Future Steps of Soft Sensor Development 162 10.6.1 Large Effort Required for Preprocessing of Industrial Data 162 10.6.2 Which Modeling Method to Choose? 163 10.6.3 Agreement of the Developed Model with Physics of the Process 163 10.6.4 Performance Deterioration of Developed Soft Sensor Model 163 11 Offline Simulation 167 11.1 What Is Offline Simulation? 167 11.2 Purpose of Offline Simulation 167 11.3 Main Task of Offline Simulation 168 11.4 Understanding Different Tuning Parameters of Offline Simulations 168 11.4.1 Tuning Parameters for CVs 169 11.4.1.1 Methods for Handling of Infeasibility 170 11.4.1.2 Priority Ranking of CVs 170 11.4.1.3 cv Give‐Up 170 11.4.1.4 cv Error Weight 170 11.4.2 Tuning Parameters for MVs 171 11.4.2.1 mv Maximum Movement Limits or Rate‐of‐Change Limits 171 11.4.2.2 Movement Weights 171 11.4.3 Tuning Parameters for Optimizer 172 11.4.3.1 Economic Optimization 172 11.4.3.2 General Form of Objective Function 173 11.4.3.3 Weighting Coefficients 173 11.4.3.4 Setting Linear Objective Coefficients 173 11.4.3.5 Optimization Horizon and Optimization Speed Factor 174 11.4.3.6 Optimization Speed Factor 174 11.4.3.7 mv Optimization Priority 174 11.4.4 Soft Limits 175 11.4.4.1 How Soft Limits Work 175 11.4.4.2 cv Soft Limits 175 11.4.4.3 mv Soft Limits 176 11.5 Different Steps to Build and Activate Simulator in an Offline PC 176 11.6 Example of Tests Carried out in Simulator 177 11.6.1 Control and Optimization Objectives 177 11.6.1.1 Test 1 178 11.6.1.2 Test 2 179 11.6.1.3 Test 3 179 11.6.1.4 Test 4 180 11.6.1.5 Test 5 180 11.6.1.6 Test 6 180 11.6.1.7 Others Tests 181 11.7 Guidelines for Choosing Tuning Parameters 181 11.7.1 Guidelines for Choosing Initial Values 181 11.7.2 How to Select Maximum Move Size and MV Movement Weights During Simulation Study 182 12 Online Deployment of MPC Application in Real Plants 183 12.1 What Is Online Deployment (Controller Commissioning)? 183 12.2 Steps for Controller Commissioning 183 12.2.1 Set up the Controller Configuration and Final Review of the Model 183 12.2.2 Build the Controller 184 12.2.3 Load Operator Station on PC Near the Panel Operator 184 12.2.4 Take MPC Controller in Line with Prediction Mode 186 12.2.5 Put the MPC Controller in Close Loop with One CV at a Time 187 12.2.6 Observe MPC Controller Performance 187 12.2.7 Put Optimizer in Line and Observe Optimizer Performance 189 12.2.8 Evaluate Overall Controller Performance 189 12.2.9 Perform Online Tuning and Troubleshooting 190 12.2.10 Train Operators and Engineers on Online Platform 190 12.2.11 Document MPC Features 190 12.2.12 Maintain the MPC Controller 191 13 Online Controller Tuning 193 13.1 What Is Online MPC Controller Tuning? 193 13.2 Basics of Online Tuning 193 13.2.1 Key Checkout Regarding Controller Performance 193 13.2.2 Steps to Troubleshoot the Problem 194 13.3 Guidelines to Choose Different Tuning Parameters 195 14 Why Do Some MPC Applications Fail? 199 14.1 What Went Wrong? 199 14.2 Failure to Build Efficient MPC Application 201 14.2.1 Historical Perspective 201 14.2.2 Capability of MPC Software to Capture Benefits 202 14.2.3 Expertise of Implementation Team 202 14.2.3.1 MPC Vendor Limitations 203 14.2.3.2 Client Limitations 204 14.2.4 Reliability of APC Project Methodology 204 14.3 Contributing Failure Factors of Postimplementation MPC Application 205 14.3.1 Technical Failure Factors 206 14.3.1.1 Lack of Performance Monitoring of MPC Application 206 14.3.1.2 Unresolved Basic Control Problems 206 14.3.1.3 Poor Tuning and Degraded Model Quality 207 14.3.1.4 Problems Related to Controller Design 207 14.3.1.5 Significant Process Modifications and Enhancement 207 14.3.2 Nontechnical Failure Factors 208 14.3.2.1 Lack of Properly Trained Personnel 208 14.3.2.2 Lack of Standards and Guidelines to MPC Support Personnel 208 14.3.2.3 Lack of Organizational Collaboration and Alignment 208 14.3.2.4 Poor Management of Control System 209 14.4 Strategies to Avoid MPC Failures 210 14.4.1 Technical Solutions 211 14.4.1.1 Development of Online Performance Monitoring of APC Applications 211 14.4.1.2 Improvement of Base Control Layer 212 14.4.1.3 Tuning Basic Controls 212 14.4.1.4 Control Performance Monitoring Software 213 14.4.2 Management Solutions 214 14.4.2.1 Training of MPC Console Operators 214 14.4.2.2 Training of MPC Control Engineers 215 14.4.2.3 Development of Corporate MPC Standards and Guidelines 216 14.4.2.4 Central Engineering Support Organization for MPC 217 14.4.3 Outsourcing Solutions 219 15 MPC Performance Monitoring 221 15.1 Why Performance Assessment of MPC Application Is Necessary 221 15.2 Types of Performance Assessment 222 15.2.1 Control Performance 222 15.2.2 Optimization Performance 222 15.2.3 Economic Performance 222 15.2.4 Intangible Performance 222 15.3 Benefit Measurement after MPC Implementation 222 15.4 Parameters to Be Monitored for MPC Performance Evaluation 223 15.4.1 Service Factors 224 15.4.2 KPI for Financial Criteria 224 15.4.3 KPI for Standard Deviation of Key Process Variable 225 15.4.3.1 Safety Parameters 225 15.4.3.2 Quality Giveaway Parameters 225 15.4.3.3 Economic Parameters 225 15.4.4 KPI for Constraint Activity 226 15.4.5 KPI for Constraint Violation 226 15.4.6 KPI for Inferential Model Monitoring 226 15.4.7 Model Quality 226 15.4.8 Limit Change Frequencies for CV/MVs 227 15.4.9 Active MV Limit 227 15.4.10 Long‐Term Performance Monitoring of MPC 227 15.5 KPIs to Troubleshoot Poor Performance of Multivariable Controls 228 15.5.1 Supporting KPIs for Low Service Factor 228 15.5.2 KPIs to Troubleshoot Cycling 229 15.5.3 KPIs for Oscillation Detection 230 15.5.4 KPIs for Regulatory Control Issues 230 15.5.5 KPIs for Measuring Operator Actions 231 15.5.6 KPIs for Measuring Process Changes and Disturbances 231 15.6 Exploitation of Constraints Handling and Maximization of MPC Benefit 231 16 Commercial MPC Vendors and Applications 235 16.1 Basic Modules and Components of Commercial MPC Software 235 16.1.1 Basic MPC Package 235 16.1.2 Data Collection Module 236 16.1.3 MPC Online Controller 236 16.1.4 Operator/ Engineer Station 237 16.1.5 System Identification Module 237 16.1.5.1 Different Modeling Options 239 16.1.5.2 Reporting and Documentation Function 239 16.1.5.3 Data Analysis and Pre‐Processing 239 16.1.6 PC‐Based Offline Simulation Package 240 16.1.7 Control Performance Monitoring and Diagnostics Software 240 16.1.7.1 Control Performance Monitoring 240 16.1.7.2 Basic Features of Performance Monitoring and Diagnostics Software 240 16.1.7.3 Performance and Benefits Metrics 241 16.1.7.4 Offline Module 241 16.1.7.5 Online Package 241 16.1.7.6 Online Reports 241 16.1.8 Soft Sensor Module (Also Called Quality Estimator Module) 242 16.1.8.1 Soft Sensor Offline Package 242 16.1.8.2 Soft Sensor Online Package 243 16.1.8.3 Soft Sensor Module Simulation Tool 243 16.2 Major Commercial MPC Software 243 16.3 AspenTech and DMCplus 244 16.3.1 Brief History of Development 244 16.3.1.1 Enhancement of DMC Technology to QDMC Technology in 1983, Regarded as Second‐Generation of MPC Technology (1980–1985) 244 16.3.1.2 Introduction of AspenTech and Evolvement of Third‐Generation MPC Technology (1985–1990) 245 16.3.1.3 Appearance of DMCplus Product with Fourth‐Generation MPC Technology (1990–2000) 245 16.3.1.4 Improvement of DMCplus Technology for Quicker Implementation in Shop Floor, Regarded as Fifth‐Generation MPC (2000–2015) 245 16.3.2 DMCplus Product Package 246 16.3.2.1 Aspen DMCplus Desktop 246 16.3.2.2 Aspen DMCplus Online 246 16.3.2.3 DMCplus Models and Identification Package 247 16.3.2.4 Aspen IQ (Soft Sensor Software) 247 16.3.2.5 Aspen Watch: AspenTech MPC Monitoring and Diagnostic Software 247 16.3.3 Distinctive Features of DMCplus Software Package 248 16.3.3.1 Automating Best Practices in Process Unit Step Testing 248 16.3.3.2 Adaptive Modeling 248 16.3.3.3 New Innovation 249 16.3.3.4 Background Step Testing 250 16.4 RMPCT by Honeywell 251 16.4.1 Brief History of Development 251 16.4.2 Honeywell MPC Product Package and Its Special Features 251 16.4.3 Key Features and Functions of RMPCT 251 16.4.3.1 Special Feature to Handle Model Error 251 16.4.3.2 Coping with Model Error 252 16.4.3.3 Funnels 252 16.4.3.4 Range Control Algorithm 252 16.4.4 Product Value Optimization Capabilities 252 16.4.5 “One‐Knob” Tuning 253 16.5 SMOC–Shell Global Solution 253 16.5.1 Evolution of Advance Process Control in Shell 253 16.5.1.1 1975–1998: The Beginnings 253 16.5.1.2 1998–2008: Shell Global Solution and Partnering with Yokogawa Era 254 16.5.1.3 2008 Onward: Shell Returns to Its Own Application 254 16.5.2 Shell MPC Product Package and Its Special Features 255 16.5.2.1 Key Characteristics of SMOC 255 16.5.2.2 Applications 255 16.5.3 SMOC Integrated Software Modules 255 16.5.3.1 AIDA Pro Offline Modeling Package 256 16.5.3.2 md Pro 256 16.5.3.3 RQE Pro 256 16.5.3.4 SMOC Pro 257 16.5.4 SMOC Claim of Superior Distinctive Features 259 16.5.4.1 Integrated Dynamic Modeling Tools and Automatic Step Tests 259 16.5.4.2 State‐of‐the‐Art Online Commissioning Tools 259 16.5.4.3 Online Tuning 259 16.5.4.4 Advance Regulatory Controls 260 16.5.4.5 Features of New Product 260 16.6 Conclusion 261 Index 263

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Book SynopsisThis textbook is an introduction to microwave engineering. The scope of this book extends from topics for a first course in electrical engineering, in which impedances are analyzed using complex numbers, through the introduction of transmission lines that are analyzed using the Smith Chart, and on to graduate level subjects, such as equivalent circuits for obstacles in hollow waveguides, analyzed using Green's Functions. This book is a virtual encyclopedia of circuit design methods. Despite the complexity, topics are presented in a conversational manner for ease of comprehension. The book is not only an excellent text at the undergraduate and graduate levels, but is as well a detailed reference for the practicing engineer. Consider how well informed an engineer will be who has become familiar with these topics as treated in High Frequency Techniques: (in order of presentation) Brief history of wireless (radio) and the Morse codeU.S. Radio Frequency AllocatTable of ContentsPreface xv Acknowledgments xvii 1 Introduction 1 1.1 Beginning of Wireless 1 1.2 Current Radio Spectrum 4 1.3 Conventions Used in This Text 8 Sections 8 Equations 8 Figures 8 Exercises 8 Symbols 8 Prefixes 10 Fonts 10 1.4 Vectors and Coordinates 11 1.5 General Constants and Useful Conversions 14 2 Review of AC Analysis and Network Simulation 16 2.1 Basic Circuit Elements 16 The Resistor 16 Ohm’s Law 18 The Inductor 19 The Capacitor 20 2.2 Kirchhoff’s Laws 22 2.3 Alternating Current (AC) Analysis 23 Ohm’s Law in Complex Form 26 2.4 Voltage and Current Phasors 26 2.5 Impedance 28 Estimating Reactance 28 Addition of Series Impedances 29 2.6 Admittance 30 Admittance Definition 30 Addition of Parallel Admittances 30 The Product over the Sum 32 2.7 LLFPB Networks 33 2.8 Decibels, dBW, and dBm 33 Logarithms (Logs) 33 Multiplying by Adding Logs 34 Dividing by Subtracting Logs 34 Zero Powers 34 Bel Scale 34 Decibel Scale 35 Decibels—Relative Measures 35 Absolute Power Levels—dBm and dBW 37 Decibel Power Scales 38 2.9 Power Transfer 38 Calculating Power Transfer 38 Maximum Power Transfer 39 2.10 Specifying Loss 40 Insertion Loss 40 Transducer Loss 41 Loss Due to a Series Impedance 42 Loss Due to a Shunt Admittance 43 Loss in Terms of Scattering Parameters 44 2.11 Real RLC Models 44 Resistor with Parasitics 44 Inductor with Parasitics 44 Capacitor with Parasitics 44 2.12 Designing LC Elements 46 Lumped Coils 46 High μ Inductor Cores—the Hysteresis Curve 47 Estimating Wire Inductance 48 Parallel Plate Capacitors 49 2.13 Skin Effect 51 2.14 Network Simulation 53 3 LC Resonance and Matching Networks 59 3.1 LC Resonance 59 3.2 Series Circuit Quality Factors 60 Q of Inductors and Capacitors 60 QE, External Q 61 QL, Loaded Q 62 3.3 Parallel Circuit Quality Factors 62 3.4 Coupled Resonators 63 Direct Coupled Resonators 63 Lightly Coupled Resonators 63 3.5 Q Matching 67 Low to High Resistance 67 Broadbanding the Q Matching Method 70 High to Low Resistance 71 4 Distributed Circuits 78 4.1 Transmission Lines 78 4.2 Wavelength in a Dielectric 81 4.3 Pulses on Transmission Lines 82 4.4 Incident and Reflected Waves 83 4.5 Reflection Coefficient 85 4.6 Return Loss 86 4.7 Mismatch Loss 86 4.8 Mismatch Error 87 4.9 The Telegrapher Equations 91 4.10 Transmission Line Wave Equations 92 4.11 Wave Propagation 94 4.12 Phase and Group Velocities 97 4.13 Reflection Coefficient and Impedance 100 4.14 Impedance Transformation Equation 101 4.15 Impedance Matching with One Transmission Line 108 4.16 Fano’s (and Bode’s) Limit 109 Type A Mismatched Loads 109 Type B Mismatched Loads 112 Impedance Transformation Not Included 113 5 The Smith Chart 119 5.1 Basis of the Smith Chart 119 5.2 Drawing the Smith Chart 124 5.3 Admittance on the Smith Chart 130 5.4 Tuning a Mismatched Load 132 5.5 Slotted-Line Impedance Measurement 135 5.6 VSWR = r 139 5.7 Negative Resistance Smith Chart 140 5.8 Navigating the Smith Chart 140 5.9 Smith Chart Software 145 5.10 Estimating Bandwidth on the Smith Chart 147 5.11 Approximate Tuning May Be Better 148 5.12 Frequency Contours on the Smith Chart 150 5.13 Using the Smith Chart without Transmission Lines 150 5.14 Constant Q Circles 151 5.15 Transmission Line Lumped Circuit Equivalent 153 6 Matrix Analysis 161 6.1 Matrix Algebra 161 6.2 Z and Y Matrices 164 6.3 Reciprocity 166 6.4 The ABCD Matrix 167 6.5 The Scattering Matrix 172 6.6 The Transmission Matrix 177 7 Electromagnetic Fields and Waves 183 7.1 Vector Force Fields 183 7.2 E and H Fields 185 7.3 Electric Field E 185 7.4 Magnetic Flux Density 187 7.5 Vector Cross Product 188 7.6 Electrostatics and Gauss’s Law 193 7.7 Vector Dot Product and Divergence 194 7.8 Static Potential Function and the Gradient 196 7.9 Divergence of the B Field 200 7.10 Ampere’s Law 201 7.11 Vector Curl 202 7.12 Faraday’s Law of Induction 208 7.13 Maxwell’s Equations 209 Maxwell’s Four Equations 209 Auxiliary Relations and Definitions 210 Visualizing Maxwell’s Equations 211 7.14 Primary Vector Operations 214 7.15 The Laplacian 215 7.16 Vector and Scalar Identities 218 7.17 Free Charge within a Conductor 219 7.18 Skin Effect 221 7.19 Conductor Internal Impedance 224 7.20 The Wave Equation 227 7.21 The Helmholtz Equations 229 7.22 Plane Propagating Waves 230 7.23 Poynting’s Theorem 233 7.24 Wave Polarization 236 7.25 EH Fields on Transmission Lines 240 7.26 Waveguides 246 General Waveguide Solution 246 Waveguide Types 250 Rectangular Waveguide Fields 251 Applying Boundary Conditions 252 Propagation Constants and Waveguide Modes 253 Characteristic Wave Impedance for Waveguides 256 Phase and Group Velocities 257 TE and TM Mode Summary for Rectangular Waveguide 257 7.27 Fourier Series and Green’s Functions 261 Fourier Series 261 Green’s Functions 263 7.28 Higher Order Modes in Circuits 269 7.29 Vector Potential 271 7.30 Retarded Potentials 274 7.31 Potential Functions in the Sinusoidal Case 275 7.32 Antennas 275 Short Straight Wire Antenna 275 Radiation Resistance 279 Radiation Pattern 280 Half-Wavelength Dipole 280 Antenna Gain 283 Antenna Effective Area 284 Monopole Antenna 285 Aperture Antennas 286 Phased Arrays 288 7.33 Path Loss 290 7.34 Electromagnetic (EM) Simulation 294 8 Directional Couplers 307 8.1 Wavelength Comparable Dimensions 307 8.2 The Backward Wave Coupler 307 8.3 Even- and Odd-Mode Analysis 309 8.4 Reflectively Terminated 3-dB Coupler 320 8.5 Coupler Specifications 323 8.6 Measurements Using Directional Couplers 325 8.7 Network Analyzer Impedance Measurements 326 8.8 Two-Port Scattering Measurements 327 8.9 Branch Line Coupler 327 8.10 Hybrid Ring Coupler 330 8.11 Wilkinson Power Divider 330 9 Filter Design 335 9.1 Voltage Transfer Function 335 9.2 Low-Pass Prototype 336 9.3 Butterworth or Maximally Flat Filter 337 9.4 Denormalizing the Prototype Response 339 9.5 High-Pass Filters 343 9.6 Bandpass Filters 345 9.7 Bandstop Filters 349 9.8 Chebyshev Filters 351 9.9 Phase and Group Delay 356 9.10 Filter Q 361 9.11 Diplexer Filters 364 9.12 Top-Coupled Bandpass Filters 367 9.13 Elliptic Filters 369 9.14 Distributed Filters 370 9.15 The Richards Transformation 374 9.16 Kuroda’s Identities 379 9.17 Mumford’s Maximally Flat Stub Filters 381 9.18 Filter Design with the Optimizer 384 9.19 Statistical Design and Yield Analysis 386 Using Standard Part Values 386 The Normal Distribution 387 Other Distributions 391 10 Transistor Amplifier Design 399 10.1 Unilateral Design 399 Evaluating S Parameters 399 Transistor Biasing 400 Evaluating RF Performance 403 10.2 Amplifier Stability 405 10.3 K Factor 409 10.4 Transducer Gain 413 10.5 Unilateral Gain Design 416 10.6 Unilateral Gain Circles 422 Input Gain Circles 422 Output Gain Circles 424 10.7 Simultaneous Conjugate Match Design 428 10.8 Various Gain Definitions 431 10.9 Operating Gain Design 433 10.10 Available Gain Design 437 10.11 Noise in Systems 442 Thermal Noise Limit 442 Other Noise Sources 444 Noise Figure of a Two-Port Network 445 Noise Factor of a Cascade 447 Noise Temperature 448 10.12 Low-Noise Amplifiers 450 10.13 Amplifier Nonlinearity 455 Gain Saturation 455 Intermodulation Distortion 456 10.14 Broadbanding with Feedback 460 10.15 Cascading Amplifier Stages 466 10.16 Amplifier Design Summary 468 Appendices A. Symbols and Units 474 B. Complex Mathematics 478 C. Diameter and Resistance of Annealed Copper Wire by Gauge Size 483 D. Properties of Some Materials 485 E. Standard Rectangular Waveguides 486 Frequently Used Relations 487 Index 491

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Book SynopsisThe definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems.Table of ContentsAbout the Authors xi Preface xiii About the Companion Website xvii Part 1 Big Data, Clouds and Internet of Things 1 1. Big Data Science and Machine Intelligence 3 1.1 Enabling Technologies for Big Data Computing 3 1.2 Social-Media, Mobile Networks and Cloud Computing 16 1.3 Big Data Acquisition and Analytics Evolution 24 1.4 Machine Intelligence and Big Data Applications 32 1.5 Conclusions 42 Homework Problems 42 References 43 2. Smart Clouds, Virtualization and Mashup Services 45 2.1 Cloud Computing Models and Services 45 2.2 Creation of Virtual Machines and Docker Containers 57 2.3 Cloud Architectures and Resources Management 65 2.4 Case Studies of IaaS, PaaS and SaaS Clouds 77 2.5 Mobile Clouds and Inter-Cloud Mashup Services 88 2.6 Conclusions 98 Homework Problems 98 References 103 3. IoT Sensing, Mobile and Cognitive Systems 105 3.1 Sensing Technologies for Internet of Things 105 3.2 IoT Interactions with GPS, Clouds and Smart Machines 111 3.3 Radio Frequency Identification (RFID) 119 3.4 Sensors, Wireless Sensor Networks and GPS Systems 124 3.5 Cognitive Computing Technologies and Prototype Systems 139 3.6 Conclusions 149 Homework Problems 150 References 152 Part 2 Machine Learning and Deep Learning Algorithms 155 4. Supervised Machine Learning Algorithms 157 4.1 Taxonomy of Machine Learning Algorithms 157 4.2 Regression Methods for Machine Learning 164 4.3 Supervised Classification Methods 171 4.4 Bayesian Network and Ensemble Methods 187 4.5 Conclusions 200 Homework Problems 200 References 203 5. Unsupervised Machine Learning Algorithms 205 5.1 Introduction and Association Analysis 205 5.2 Clustering Methods without Labels 213 5.3 Dimensionality Reduction and Other Algorithms 225 5.4 How to Choose Machine Learning Algorithms? 233 5.5 Conclusions 243 Homework Problems 243 References 247 6. Deep Learning with Artificial Neural Networks 249 6.1 Introduction 249 6.2 Artificial Neural Networks (ANN) 256 6.3 Stacked Auto Encoder and Deep Belief Network 264 6.4 Convolutional Neural Networks (CNN) and Extensions 277 6.5 Conclusions 287 Homework Problems 288 References 291 Part 3 Big Data Analytics for Health-Care and Cognitive Learning 293 7. Machine Learning for Big Data in Healthcare Applications 295 7.1 Healthcare Problems and Machine Learning Tools 295 7.2 IoT-based Healthcare Systems and Applications 299 7.3 Big Data Analytics for Healthcare Applications 310 7.4 Emotion-Control Healthcare Applications 322 7.5 Conclusions 335 Homework Problems 336 References 339 8. Deep Reinforcement Learning and Social Media Analytics 343 8.1 Deep Learning Systems and Social Media Industry 343 8.2 Text and Image Recognition using ANN and CNN 348 8.3 DeepMind with Deep Reinforcement Learning 362 8.4 Data Analytics for Social-Media Applications 375 8.5 Conclusions 390 Homework Problems 391 References 393 Index 395

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Book SynopsisComprehensive Handbook Demystifies 5G for Technical and Business Professionals in Mobile Telecommunication Fields Much is being said regarding the possibilities and capabilities of the emerging 5G technology, as the evolution towards 5G promises to transform entire industries and many aspects of our society. 5G for the Connected World offers a comprehensive technical overview that telecommunication professionals need to understand and take advantage of these developments. The book offers a wide-ranging coverage of the technical aspects of 5G (with special consideration of the 3GPP Release 15 content), how it enables new services and how it differs from LTE. This includes information on potential use cases, aspects of radio and core networks, spectrum considerations and the services primarily driving 5G development and deployment. The text also looks at 5G in relation to the Internet of Things, machine to machine communication and technical enablers such as LTE-M, NB-IoT and EC-GSM. Table of ContentsAbout the Editors xvii List of Contributors xix Foreword by Tommi Uitto xxi Foreword by Karri Kuoppamaki xxiii Preface xxv Acknowledgements xxvii Introduction xxix Terminology xxxi 1 Drivers and Motivation for 5G 1Betsy Covell and Rainer Liebhart 1.1 Drivers for 5G 1 1.2 ITU-R and IMT 2020 Vision 3 1.3 NGMN (Next Generation Mobile Networks) 5 1.4 5GPPP (5G Public-Private Partnership) 8 1.5 Requirements for Support of Known and New Services 9 1.6 5G Use Cases 19 1.7 Business Models 26 1.8 Deployment Strategies 28 1.9 3GPP Role and Timelines 30 References 34 2 Wireless Spectrum for 5G 35Juho Pirskanen, Karri Ranta-aho, Rauno Ruismäki and Mikko Uusitalo 2.1 Current Spectrum for Mobile Communication 35 2.2 Spectrum Considerations for 5G 35 2.3 Identified New Spectrum 37 2.4 Spectrum Regulations 38 2.5 Characteristics of Spectrum Available for 5G 43 2.6 NR Bands Defined by 3GPP 46 References 48 3 Radio Access Technology 51Sami Hakola, Toni Levanen, Juho Pirskanen, Karri Ranta-aho, Samuli Turtinen, Keeth Jayasinghe and Fred Vook 3.1 Evolution Toward 5G 51 3.2 Basic Building Blocks 56 3.3 Downlink Physical Layer 83 3.4 Uplink Physical Layer 92 3.5 Radio Protocols 96 3.6 Mobile Broadband 117 References 124 4 Next Generation Network Architecture 127Devaki Chandramouli, Subramanya Chandrashekar, AndreasMaeder, Tuomas Niemela, Thomas Theimer and Laurent Thiebaut 4.1 Drivers and Motivation for a New Architecture 127 4.2 Architecture Requirements and Principles 130 4.3 5G System Architecture 139 4.4 NG RAN Architecture 149 4.5 Non-Standalone and Standalone Deployment Options 158 4.6 Identifiers 161 4.7 Network Slicing 163 4.8 Multi-Access Edge Computing 171 4.9 Data Storage Architecture 173 4.10 Network Capability Exposure 180 4.11 Interworking and Migration 182 4.12 Non-3GPP Access 189 4.13 Fixed Mobile Convergence 193 4.14 Network Function Service Framework 196 4.15 IMS Services 203 4.16 Emergency Services 205 4.17 Location Services 207 4.18 Short Message Service 208 4.19 Public Warning System 210 4.20 Protocol Stacks 212 4.21 Charging 218 4.22 Summary and Outlook of 5G System Features 219 4.23 Terminology and Definitions 221 References 222 5 Access Control and Mobility Management 225Devaki Chandramouli, Subramanya Chandrashekar, JarmoMakinen,Mikko Säily and Sung HwanWon 5.1 General Principles 225 5.2 Mobility States and Functionalities 228 5.3 Initial Access and Registration 234 5.4 Connected Mode Mobility 238 5.5 Idle Mode mobility and UE Reachability 261 5.6 RRC Inactive State mobility and UE Reachability 265 5.7 Beam Level Mobility 268 5.8 Support for High Speed Mobility 270 5.9 Support for Ultralow Latency and Reliable Mobility 273 5.10 UE Mobility Restrictions and Special Modes 276 5.11 Inter-System (5GS-EPS) Mobility 277 5.12 Outlook 280 References 281 6 Sessions, User Plane, and QoS Management 283Devaki Chandramouli, Thomas Theimer and Laurent Thiebaut 6.1 Introduction 283 6.2 Basic Principles of PDU Sessions 283 6.3 Ultra-reliable Low Latency Communication 293 6.4 QoS Management in 5GS 295 6.5 User Plane Transport 301 6.6 Policy Control and Application Impact on Traffic Routing 302 6.7 Session Management 306 6.8 SMF Programming UPF Capabilities 309 References 310 7 Security 311Peter Schneider 7.1 Drivers, Requirements and High-Level Security Vision 311 7.2 Overall 5G Security Architecture 316 7.3 3GPP Specific Security Mechanisms 319 7.4 SDN Security 327 7.5 NFV Security 330 7.6 Network Slicing Security 332 7.7 Private Network Infrastructure 335 References 335 8 Critical Machine Type Communication 337Zexian Li and Rainer Liebhart 8.1 Introduction 337 8.2 Key Performance Indicators 340 8.3 Solutions 341 References 374 9 Massive Machine Type Communication and the Internet of Things 377Devaki Chandramouli, Betsy Covell, Volker Held, Hannu Hietalahti, Jürgen Hofmann and Rapeepat Ratasuk 9.1 Massive M2M Versus IoT 377 9.2 Requirements and Challenges 379 9.3 Technology Evolution 382 9.4 EPS Architecture Evolution 384 9.5 Cellular Internet of Things 391 9.6 GERAN 405 9.7 LTE-M 418 9.8 NB-IoT 422 9.9 5G for M2M 428 9.10 Comparison of EPS and 5GS 431 9.11 Future Enhancements 433 9.12 Other Technologies 438 References 438 10 Summary and Outlook 441Rainer Liebhart and Devaki Chandramouli 10.1 Summary 441 10.2 Outlook 442 Appendix of 3GPP Reference Points 447 Index 451

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Book SynopsisThe definitive guide to developing robust content delivery networks This book examines the real-world engineering challenges of developing robust content delivery networks (CDNs) and provides the tools required to overcome those challenges and to ensure high-quality content delivery that fully satisfies operators' and consumers'' commercial objectives. It is informed by the author's two decades of experience building and delivering large, mission-critical live video, webcasts, and radio streaming, online and over private IP networks. Following an overview of the field, the book cuts to the chase with in-depth discussionslaced with good-natured humorof a wide range of design considerations for different network topologies. It begins with a description of the author''s own requirement filtration processes. From there it moves on to initial sketches, through considerations of stakeholder roles and responsibilities, to the complex challenges of managing change in esTable of ContentsFrontispiece xiii Topics Include xiii About the Book xiv Synposis xiv Unique Perspective xv Market Need xvi Audience xvii 1 Welcome 1 1.1 A Few Words of Introduction 1 1.2 The “Why” of this Book 2 1.3 Relevant Milestones of the Personal Voyage 3 2 Context and Orientation 9 2.1 History of Streaming 10 2.1.1 Foundations – What does “Streaming” Really Mean? 12 2.1.2 Streaming 13 2.1.3 Related Network Models 16 2.1.4 Physical Network Considerations 16 2.1.5 Internet Layer Considerations 17 2.1.6 Transport Layer Considerations 17 2.1.7 Applications – Transport Protocols 18 2.1.8 Protocol Evolution 19 2.1.9 Format Evolution 25 2.2 Industry Evolution 25 2.2.1 “Stack Creep” 26 2.2.2 Real World – Blue Chips and Video Delivery Networks 26 2.3 Consumer Adoption 29 2.3.1 The Audience 29 2.3.2 Traditional Ratings Companies and Audience Measurement 32 2.3.3 Streaming Media and Measurement 34 2.3.4 Predictions of Others 37 2.3.5 The Pending Collapse of the Value of Broadcasting to Advertisers 41 2.3.6 “Device Effect” and Formats 41 2.3.7 Video Formats (in Particular, Multicast and UDP) and Network Architecture 43 2.3.8 Discovery, Curation, and Social Media 45 2.4 Encode > Serve > Play 54 2.4.1 The Basic Building Blocks 54 2.4.2 The Acacia Patent 55 2.4.3 Akamai vs. Limelight 57 2.4.4 Standards, Standards, Standards, … 58 2.4.5 D]Book Connected TV Standards from the Digital Television Group 60 2.4.6 The CoDec Concerns 61 2.5 What is a CDN: A Simple Model 63 2.5.1 Setting the Scene for CDNs 63 2.5.2 CDNs as Money Savers 66 2.5.3 Request Routing 67 2.5.4 CDN Brokerage 69 2.5.5 SaaS Models within the CDN Ecosystems 70 2.6 Cloud Inside – New Generation 75 2.7 The Three Generations of CDN 76 2.8 Software Definition 82 2.8.1 Multicore CPU and Functional Programming 86 2.8.2 Functional Programming and Containers 86 2.9 “Service Velocity” and the Operator 87 3 Workflows 89 3.1 Live Event Focus 92 3.1.1 Approaches to Webcasting 93 3.1.2 Think Before You Start – Your Client Probably Hasn’t! 94 3.1.3 Budgets 95 3.1.4 Objectives – Quality vs. Reliability 97 3.1.5 Production Principles 98 3.2 Backhaul/Contribution and Acquisition 102 3.2.1 Broadcast 104 3.2.2 Wire 104 3.2.3 Wireless 107 3.2.4 Satellite 108 3.2.5 3g/4G CellMux 109 3.2.6 Reliable UDP and HTTP/UDP Solutions 111 3.2.7 Throughput vs. Goodput 112 3.3 Cloud Saas 113 3.3.1 In Workflow “Treatment” (Transcode/Transmux, etc.) 114 3.3.2 DVR Workflows 117 3.3.3 Catch]up Workflows 119 3.3.4 VOD Workflows 121 4 Publishing 125 4.1 Publishers, OVPs, CDNs, and MCNs 126 4.2 Small Objects, Large Objects, or Continuous Streams 129 4.2.1 Compression 132 4.2.2 The “Quality Question” … 134 4.2.3 Latency 136 4.2.4 Application, Site, Web, and Games Acceleration 137 4.3 Desktop and Device Delivery Applications 138 4.3.1 Standalone Media Players and Applications 138 4.3.2 Video Tags in HTML5 141 4.3.3 WebRTC – Beyond HTML5 142 4.4 Request Routing (The Dark Art of the CDN) 142 4.5 Logging Analytics and the Devil in the Detail 143 5 Service Velocity 145 6 Charging for IP]Delivered Content 151 6.1 Lessons from the Music Industry 151 6.2 Success Cases 153 6.2.1 YouTube 154 6.2.2 Netflix 155 6.2.3 On the Horizon 156 6.3 Failure Cases 158 6.3.1 Scour.net 158 6.3.2 mp3.com 159 6.3.3 Napster 160 6.3.4 Broadcast.com 160 6.3.5 The “Yacht Projects” 162 6.4 General Commentary on Commercial Models 163 6.4.1 Cable TV 164 6.4.2 IPTV 165 6.4.3 OTT Pureplay + Operator CDN 166 6.4.4 Fog Distribution 167 6.4.5 Variation from Live Linear to VOD, and Everything in Between 168 6.4.6 DRM 169 6.4.7 Watermarking 171 7 Competition and the Regulatory Environment 175 7.1 ISOC, ITU, and WSIS 176 7.2 Policy – Net Neutrality 179 7.3 Value Chain Alignment with QoS and SLA Propositions 181 7.4 Layer] 2 Workaround? 181 8 Cultural Change 183 8.1 Traditional Broadcasters 183 8.2 The Millenial Subscriber 185 8.3 ISP and Content Providers 186 8.4 Telco and Telecoms 188 8.5 Content Providers 188 9 Preparing for Change in Your Design 191 9.1 Preface and Philosophy 191 9.2 Models, Diagrams, and Schematics 193 9.3 How to do a Good Diagram? 193 9.4 Scenario Planning 194 9.5 Risk, Responsibility, and Reassurance 196 9.6 Optimization and Upsell 196 9.7 Value Creation/Agility 197 9.8 Expectation Management 197 10 Multicast – the Sleeping Giant 199 10.1 Multicast Recap 199 10.1.1 Basics 199 10.1.2 Routing Protocols 200 10.1.3 Flood, Prune, Storms, and a Bad Taste 201 10.1.4 Commercial Outcome 201 10.2 What Happens Now? 202 10.3 To Singularity and Beyond 204 11 Deep]Dives (Case Studies) 207 11.1 Hitting the TV Screen – IPTV/Hybrid TV and OTT 207 11.1.1 The Taxonomy of OTT Video 210 11.1.2 Arqiva Connect and Freeview Plus 214 11.2 Creating Nasdaq’s Cloud]Based Virtual Workflow 217 11.2.1 The Genesis of a Virtual Workflow 218 11.2.2 The Technology Behind the Workflow 219 11.2.3 Why Amazon EC2? 220 11.2.4 What Sort of Scaling Issues did You Face? 222 11.2.5 How about SLA? 222 11.2.6 What about Signal Acquisition? 222 11.2.7 What about OS Choices and Stacks? 223 11.2.8 How Is the System Controlled? 223 11.2.9 How Does it Report? 224 12 Wrap Up 225 Index 229

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Book SynopsisA comprehensive guide that addresses the theory and practice of spatial audio This book provides readers with the principles and best practices in spatial audio signal processing. It describes how sound fields and their perceptual attributes are captured and analyzed within the time-frequency domain, how essential representation parameters are coded, and how such signals are efficiently reproduced for practical applications. The book is split into four parts starting with an overview of the fundamentals. It then goes on to explain the reproduction of spatial sound before offering an examination of signal-dependent spatial filtering. The book finishes with coverage of both current and future applications and the direction that spatial audio research is heading in. Parametric Time-frequency Domain Spatial Audio focuses on applications in entertainment audio, including music, home cinema, and gamingcovering the capturing and reproduction of spatial sound as Table of ContentsContents List of Contributors xiii Preface xv About the Companion Website xix Part I Analysis and Synthesis of Spatial Sound 1 Time–Frequency Processing: Methods and Tools 3Juha Vilkamo and Tom Ba¨ckstro¨m 1.1 Introduction 3 1.2 Time–Frequency Processing 4 1.2.1 Basic Structure 4 1.2.2 Uniform Filter Banks 5 1.2.3 Prototype Filters and Modulation 6 1.2.4 A Robust Complex-Modulated Filter Bank, and Comparison with STFT 8 1.2.5 Overlap-Add and Windowing 12 1.2.6 Example Implementation of a Robust Filter Bank in Matlab 13 1.2.7 Cascaded Filters 15 1.3 Processing of Spatial Audio 16 1.3.1 Stochastic Estimates 17 1.3.2 Decorrelation 18 1.3.3 Optimal and Generalized Solution for Spatial Sound Processing Using Covariance Matrices 19 References 23 2 Spatial Decomposition by Spherical Array Processing 25David Lou Alon and Boaz Rafaely 2.1 Introduction 25 2.2 Sound Field Measurement by a Spherical Array 26 2.3 Array Processing and Plane-Wave Decomposition 26 2.4 Sensitivity to Noise and Standard Regularization Methods 29 2.5 Optimal Noise-Robust Design 32 2.5.1 PWD Estimation Error Measure 32 2.5.2 PWD Error Minimization 34 2.5.3 R-PWD Simulation Study 35 2.6 Spatial Aliasing and High Frequency Performance Limit 37 2.7 High Frequency Bandwidth Extension by Aliasing Cancellation 39 2.7.1 Spatial Aliasing Error 39 2.7.2 AC-PWD Simulation Study 40 2.8 High Performance Broadband PWD Example 42 2.8.1 Broadband Measurement Model 42 2.8.2 Minimizing Broadband PWD Error 42 2.8.3 BB-PWD Simulation Study 44 2.9 Summary 45 2.10 Acknowledgment 46 References 46 3 Sound Field Analysis Using Sparse Recovery 49Craig T. Jin, Nicolas Epain, and Tahereh Noohi 3.1 Introduction 49 3.2 The Plane-Wave Decomposition Problem 50 3.2.1 Sparse Plane-Wave Decomposition 51 3.2.2 The Iteratively Reweighted Least-Squares Algorithm 51 3.3 Bayesian Approach to Plane-Wave Decomposition 53 3.4 Calculating the IRLS Noise-Power Regularization Parameter 55 3.4.1 Estimation of the Relative Noise Power 56 3.5 Numerical Simulations 58 3.6 Experiment: Echoic Sound Scene Analysis 59 3.7 Conclusions 65 Appendix 65 References 66 Part II Reproduction of Spatial Sound 69 Overview of Time–Frequency Domain Parametric Spatial Audio Techniques 71Archontis Politis, Symeon Delikaris-Manias, and Ville Pulkki 4.1 Introduction 71 4.2 Parametric Processing Overview 73 4.2.1 Analysis Principles 74 4.2.2 Synthesis Principles 75 4.2.3 Spatial Audio Coding and Up-Mixing 76 4.2.4 Spatial Sound Recording and Reproduction 78 4.2.5 Auralization of Measured Room Acoustics and Spatial Rendering of Room Impulse Responses 81 References 82 5 First-Order Directional Audio Coding (DirAC) 89Ville Pulkki, Archontis Politis, Mikko-Ville Laitinen, Juha Vilkamo, and Jukka Ahonen 5.1 Representing Spatial Sound with First-Order B-Format Signals 89 5.2 Some Notes on the Evolution of the Technique 92 5.3 DirAC with Ideal B-Format Signals 94 5.4 Analysis of Directional Parameters with Real Microphone Setups 97 5.4.1 DOA Analysis with Open 2D Microphone Arrays 97 5.4.2 DOA Analysis with 2D Arrays with a Rigid Baffle 99 5.4.3 DOA Analysis in Underdetermined Cases 101 5.4.4 DOA Analysis: Further Methods 102 5.4.5 Effect of Spatial Aliasing and Microphone Noise on the Analysis of Diffuseness 103 5.5 First-Order DirAC with Monophonic Audio Transmission 105 5.6 First-Order DirAC with Multichannel Audio Transmission 106 5.6.1 Stream-Based Virtual Microphone Rendering 106 5.6.2 Evaluation of Virtual Microphone DirAC 109 5.6.3 Discussion of Virtual Microphone DirAC 111 5.6.4 Optimized DirAC Synthesis 111 5.6.5 DirAC-Based Reproduction of Spaced-Array Recordings 114 5.7 DirAC Synthesis for Headphones and for Hearing Aids 117 5.7.1 Reproduction of B-Format Signals 117 5.7.2 DirAC in Hearing Aids 118 5.8 Optimizing the Time–Frequency Resolution of DirAC for Critical Signals 119 5.9 Example Implementation 120 5.9.1 Executing DirAC and Plotting Parameter History 122 5.9.2 DirAC Initialization 125 5.9.3 DirAC Runtime 131 5.9.4 Simplistic Binaural Synthesis of Loudspeaker Listening 136 5.10 Summary 137 References 138 6 Higher-Order Directional Audio Coding 141Archontis Politis and Ville Pulkki 6.1 Introduction 141 6.2 Sound Field Model 144 6.3 Energetic Analysis and Estimation of Parameters 145 6.3.1 Analysis of Intensity and Diffuseness in the Spherical Harmonic Domain 146 6.3.2 Higher-Order Energetic Analysis 147 6.3.3 Sector Profiles 149 6.4 Synthesis of Target Setup Signals 151 6.4.1 Loudspeaker Rendering 152 6.4.2 Binaural Rendering 155 6.5 Subjective Evaluation 157 6.6 Conclusions 157 References 158 7 Multi-Channel Sound Acquisition Using a Multi-Wave Sound Field Model 161Oliver Thiergart and Emanue¨l Habets 7.1 Introduction 161 7.2 Parametric Sound Acquisition and Processing 163 7.2.1 Problem Formulation 163 7.2.2 Principal Estimation of the Target Signal 166 7.3 Multi-Wave Sound Field and Signal Model 167 7.3.1 Direct Sound Model 168 7.3.2 Diffuse Sound Model 169 7.3.3 Noise Model 169 7.4 Direct and Diffuse Signal Estimation 170 7.4.1 Estimation of the Direct Signal Ys(k, n) 170 7.4.2 Estimation of the Diffuse Signal Yd(k, n) 176 7.5 Parameter Estimation 179 7.5.1 Estimation of the Number of Sources 179 7.5.2 Direction of Arrival Estimation 181 7.5.3 Microphone Input PSD Matrix 181 7.5.4 Noise PSD Estimation 182 7.5.5 Diffuse Sound PSD Estimation 182 7.5.6 Signal PSD Estimation in Multi-Wave Scenarios 185 7.6 Application to Spatial Sound Reproduction 186 7.6.1 State of the Art 186 7.6.2 Spatial Sound Reproduction Based on Informed Spatial Filtering 187 7.7 Summary 194 References 195 8 Adaptive Mixing of Excessively Directive and Robust Beamformers for Reproduction of Spatial Sound 201Symeon Delikaris-Manias and Juha Vilkamo 8.1 Introduction 201 8.2 Notation and Signal Model 202 8.3 Overview of the Method 203 8.4 Loudspeaker-Based Spatial Sound Reproduction 204 8.4.1 Estimation of the Target Covariance Matrix Cy 204 8.4.2 Estimation of the Synthesis Beamforming Signals Ws 206 8.4.4 Processing the Synthesis Signals (Wsx) to Obtain the Target Covariance Matrix Cy 206 Spatial Energy Distribution 207 8.4.5 Listening Tests 208 8.5 Binaural-Based Spatial Sound Reproduction 209 8.5.1 Estimation of the Analysis and Synthesis Beamforming Weight Matrices 210 8.5.2 Diffuse-Field Equalization of HRTFs 210 8.5.3 Adaptive Mixing and Decorrelation 211 8.5.4 Subjective Evaluation 211 8.6 Conclusions 212 References 212 9 Source Separation and Reconstruction of Spatial Audio Using Spectrogram Factorization 215Joonas Nikunen and Tuomas Virtanen 9.1 Introduction 215 9.2 Spectrogram Factorization 217 9.2.1 Mixtures of Sounds 217 9.2.2 Magnitude Spectrogram Models 218 9.2.3 Complex-Valued Spectrogram Models 221 9.2.4 Source Separation by Time–Frequency Filtering 225 9.3 Array Signal Processing and Spectrogram Factorization 226 9.3.1 Spaced Microphone Arrays 226 9.3.2 Model for Spatial Covariance Based on Direction of Arrival 227 9.3.3 Complex-Valued NMF with the Spatial Covariance Model 229 9.4 Applications of Spectrogram Factorization in Spatial Audio 231 9.4.1 Parameterization of Surround Sound: Upmixing by Time–Frequency Filtering 231 9.4.2 Source Separation Using a Compact Microphone Array 233 9.4.3 Reconstruction of Binaural Sound Through Source Separation 238 9.5 Discussion 243 9.6 Matlab Example 243 References 247 Part III Signal-Dependent Spatial Filtering 251 10 Time–Frequency Domain Spatial Audio Enhancement 253Symeon Delikaris-Manias and Pasi Pertila 10.1 Introduction 253 10.2 Signal-Independent Enhancement 254 10.3 Signal-Dependent Enhancement 255 10.3.1 Adaptive Beamformers 255 10.3.2 Post-Filters 257 10.3.3 Post-Filter Types 257 10.3.4 Estimating Post-Filters with Machine Learning 259 10.3.5 Post-Filter Design Based on Spatial Parameters 259 References 261 11 Cross-Spectrum-Based Post-Filter Utilizing Noisy and Robust Beamformers 265Symeon Delikaris-Manias and Ville Pulkki 11.1 Introduction 265 11.2 Notation and Signal Model 267 11.2.1 Virtual Microphone Design Utilizing Pressure Microphones 268 11.3 Estimation of the Cross-Spectrum-Based Post-Filter 269 11.3.1 Post-Filter Estimation Utilizing Two Static Beamformers 270 11.3.2 Post-Filter Estimation Utilizing a Static and an Adaptive Beamformer 272 11.3.3 Smoothing Techniques 277 11.4 Implementation Examples 279 11.4.1 Ideal Conditions 279 11.4.2 Prototype Microphone Arrays 281 11.5 Conclusions and Further Remarks 283 11.6 Source Code 284 References 287 12 Microphone-Array-Based Speech Enhancement Using Neural NetworksPasi Pertila 291 12.1 Introduction 291 12.2 Time–Frequency Masks for Speech Enhancement Using Supervised Learning 293 12.2.1 Beamforming with Post-Filtering 293 12.2.2 Overview of Mask Prediction 294 12.2.3 Features for Mask Learning 295 12.2.4 Target Mask Design 297 12.3 Artificial Neural Networks 298 12.3.1 Learning the Weights 299 12.3.2 Generalization 301 12.3.3 Deep Neural Networks 305 12.4 Mask Learning: A Simulated Example 305 12.4.1 Feature Extraction 306 12.4.2 Target Mask Design 306 12.4.3 Neural Network Training 307 12.4.4 Results 308 12.5 Mask Learning: A Real-World Example 310 12.5.1 Brief Description of the Third CHiME Challenge Data 310 12.5.2 Data Processing and Beamforming 312 12.5.3 Description of Network Structure, Features, and Targets 312 12.5.4 Mask Prediction Results and Discussion 314 12.5.5 Speech Enhancement Results 316 12.6 Conclusions 318 12.7 Source Code 318 12.7.1 Matlab Code for Neural-Network-Based Sawtooth Denoising Example 318 12.7.2 Matlab Code for Phase Feature Extraction 321 References 324 Part IV Applications 327 13 Upmixing and Beamforming in Professional Audio 329Christof Faller 13.1 Introduction 329 13.2 Stereo-to-Multichannel Upmix Processor 329 13.2.1 Product Description 329 13.2.2 Considerations for Professional Audio and Broadcast 331 13.2.3 Signal Processing 332 13.3 Digitally Enhanced Shotgun Microphone 336 13.3.1 Product Description 336 13.3.2 Concept 336 13.3.3 Signal Processing 336 13.3.4 Evaluations and Measurements 339 13.4 Surround Microphone System Based on Two Microphone Elements 341 13.4.1 Product Description 341 13.4.2 Concept 344 13.5 Summary 345 References 345 14 Spatial Sound Scene Synthesis and Manipulation for Virtual Reality and Audio Effects 347Ville Pulkki, Archontis Politis, Tapani Pihlajama¨ki, and Mikko-Ville Laitinen 14.1 Introduction 347 14.2 Parametric Sound Scene Synthesis for Virtual Reality 348 14.2.1 Overall Structure 348 14.2.2 Synthesis of Virtual Sources 350 14.2.3 Synthesis of Room Reverberation 352 14.2.4 Augmentation of Virtual Reality with Real Spatial Recordings 352 14.2.5 Higher-Order Processing 353 14.2.6 Loudspeaker-Signal Bus 354 14.3 Spatial Manipulation of Sound Scenes 355 14.3.1 Parametric Directional Transformations 356 14.3.2 Sweet-Spot Translation and Zooming 356 14.3.3 Spatial Filtering 356 14.3.4 Spatial Modulation 357 14.3.5 Diffuse Field Level Control 358 14.3.6 Ambience Extraction 359 14.3.7 Spatialization of Monophonic Signals 360 14.4 Summary 360 References 361 15 Parametric Spatial Audio Techniques in Teleconferencing and Remote Presence 363Anastasios Alexandridis, Despoina Pavlidi, Nikolaos Stefanakis, and Athanasios Mouchtaris 15.1 Introduction and Motivation 363 15.2 Background 365 15.3 Immersive Audio Communication System (ImmACS) 366 15.3.1 Encoder 366 15.3.2 Decoder 373 15.4 Capture and Reproduction of Crowded Acoustic Environments 376 15.4.1 Sound Source Positioning Based on VBAP 376 15.4.2 Non-Parametric Approach 377 15.4.3 Parametric Approach 379 15.4.4 Example Application 382 15.5 Conclusions 384 References 384 Index 387

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Book SynopsisA novel approach to decision engineering, with a verified framework for modeling human reasoning Soft Computing Evaluation Logic provides an in-depth examination of evaluation decision problems and presents comprehensive guidance toward the use of the Logic Scoring of Preference (LSP) method in modeling complex decision criteria. Fully aligned with current developments in computational intelligence, the discussion covers the design and use of LSP criteria for evaluation and comparison in diverse areas, such as search engines, medical conditions, real estate, space management, habitat mitigation projects in ecology, and land use and residential development suitability maps, with versatile transfer to other similar decision-modeling contexts. Human decision making is rife with fuzziness, imprecision, uncertainty, and half-truthsyet humans make evaluation decisions every day. In this book, such decision processes are observed, analyzed, and modeled. The resuTable of ContentsPreface xvii About the Companion Website xxiii Previous Publications xxiv Acknowledgments xxv List of Symbols and Abbreviations xxvii Part One EVALUATION DECISION PROBLEMS 1 1.1 Intuitive Evaluation as a Logic Decision Process 5 1.1.1 Main Observable Steps of the Intuitive Evaluation Process 6 1.1.2 Subjective and Objective Components in Evaluation 18 1.2 Quantitative Evaluation—An Introductory Example 21 1.2.1 Stakeholders and Their Goals 21 1.2.2 Attributes 22 1.2.3 Attribute Criteria 23 1.2.4 Simple Direct Ranking 27 1.2.5 Aggregation of Attribute Suitability Degrees 29 1.2.6 Using Cost and Suitability to Compute the Overall Value 32 1.3 Drawbacks of Simple Additive and Multiplicative Scoring and Utility Models 35 1.3.1 Simple Additive Scoring: The Irresistible Attractiveness of Simplicity 36 1.3.2 Simple Multiplicative Scoring 45 1.3.3 Logic Unsuitability of Scoring and Utility Theory Models in Professional Evaluation 47 1.4 Introduction to Professional Quantitative Evaluation 51 1.4.1 Five Fundamental Types of Professional Evaluation Problems 51 1.4.2 A Survey of Typical Professional Evaluation Problems 54 1.4.3 Components of Methodology for Professional Quantitative Evaluation 58 Part Two GRADED LOGIC AND AGGREGATION 63 2.1 Graded Logic as a Generalization of Classical Boolean Logic 69 2.1.1 Aggregators and Their Classification 70 2.1.1.1 Means 71 2.1.1.2 General Aggregation Functions 71 2.1.1.3 Logic Aggregators 73 2.1.1.4 Triangular Norms and Conorms 73 2.1.2 How Do Human Beings Aggregate Subjective Categories? 75 2.1.3 Definition and Classification of Logic Aggregators 85 2.1.4 Logic Bisection, Trisection, and Quadrisection of the Unit Hypercube 92 2.1.5 Propositions, Value Statements, Graded Logic, and Fuzzy Logic 95 2.1.6 Classical Bivalent Boolean Logic 100 2.1.7 Six Generalizations of Bivalent Boolean Logic 108 2.1.7.1 Expansion of Function Domain 109 2.1.7.2 Expansion of Logic Domain 111 2.1.7.3 Expansion of Annihilator Adjustability 112 2.1.7.4 Expansion of Semantic Domain 115 2.1.7.5 Expansion of Compensative Logic Functions 117 2.1.7.6 Expansion of the Range of Andness/Orness from Drastic Conjunction to Drastic Disjunction 118 2.1.8 GL Conjecture: Ten Necessary and Sufficient GL Functions 123 2.1.9 Basic Idempotent GL Aggregators 127 2.1.10 A Summary of Differences between Graded Logic and Bivalent Boolean Logic 134 2.1.11 Relationships between Graded Logic, Perceptual Computing, and Fuzzy Logic 136 2.1.12 A Brief History of Graded Logic 142 2.2 Observable Properties of Human Evaluation Logic 147 2.2.1 Perceptual Computer and Its Basic Properties 152 2.2.2 Simultaneity and Substitutability in Evaluation Models 177 2.2.3 Basic Semantic Aspects of Evaluation Logic Reasoning 190 2.2.4 Multipolarity: Grouping and Aggregation of Semantically Heterogeneous Inputs 212 2.2.5 Grouping and Aggregation of Semantically Homogeneous Inputs 218 2.2.6 Imprecision, Incompleteness, Logic Inconsistency, and Errors 222 2.3 Andness and Orness 237 2.3.1 A General Definition of Andness/Orness 237 2.3.2 Local Andness and Orness in the Simplest Case of Two Variables 239 2.3.3 Variability of Local Andness 242 2.3.4 Mean Local Andness and Orness in the Case of Two Variables 248 2.3.5 Local and Mean Local Andness and Orness in the Case of n Variables 251 2.3.6 Global Andness and Orness 253 2.3.7 Mean Global Andness/Orness Theorems and Their Applications 272 2.3.8 Geometric Interpretations of Andness and Orness 275 2.4 Graded Conjunction/Disjunction and Logic Modeling of Simultaneity and Substitutability 283 2.4.1 Definitions and Basic Mathematical Properties of Logic Aggregators 284 2.4.2 Classification of Conjunctive and Disjunctive Logic Aggregators 295 2.4.3 Properties of Means Used in Logic Aggregation 298 2.4.4 Algebraic Properties of Aggregators Based on Weighted Power Means 304 2.4.5 Logic Aggregators Based on Weighted Means with Adjustable Andness/Orness 313 2.4.6 Selection and Use of the Threshold Andness Aggregator 318 2.4.7 Andness-Directed Interpolative GCD Aggregators 327 2.4.8 Uniform and Nonuniform Interpolative GCD Aggregators 334 2.4.8.1 The Uniform Interpolative GCD Aggregator (UGCD) 334 2.4.8.2 An Extremely Soft Interpolative Aggregator 338 2.4.8.3 An Extremely Hard Interpolative Aggregator 338 2.4.9 Extending GCD to Include Hyperconjunction and Hyperdisjunction 342 2.4.10 From Drastic Conjunction to Drastic Disjunction: A General GCD Aggregator 347 2.4.11 Gamma Aggregators versus Extended GCD Aggregators 348 2.4.11.1 Multiplicative and Additive Gamma Aggregators 351 2.4.11.2 Comparison of Gamma Aggregators and GCD 355 2.4.12 Four Main Families of GCD Aggregators and Sixteen Conditions They Must Satisfy 361 2.5 The Percept of Importance and the Use of Weights 367 2.5.1 Multiplicative, Implicative, and Exponential Weights as Importance Quantifiers 369 2.5.1.1 Multiplicative Weights 370 2.5.1.2 Implicative Weights and the Weighted Conjunction/Disjunction 374 2.5.1.3 Exponential Weights 390 2.5.2 Impact of Weights on Aggregation Results 393 2.5.3 Semantic Components in Logic Aggregation Models 398 2.5.4 Seven Techniques for Weight Adjustment 402 2.5.4.1 Importance Decomposition Method 402 2.5.4.2 Direct Weight Assessment 405 2.5.4.3 Weights Based on Ranking 405 2.5.4.4 Weights Based on Menu 407 2.5.4.5 Collective Weight Determination 409 2.5.4.6 Weights Obtained from Pairwise Comparisons 411 2.5.4.7 Weights Based on Preferential Neuron Training 414 2.5.5 Multivariate Weighted Aggregation Based on Binary Aggregation Trees 417 2.6 Partial Absorption: A Fundamental Asymmetric Aggregator 429 2.6.1 Conjunctive Partial Absorption 430 2.6.2 Disjunctive Partial Absorption 436 2.6.3 Visualizing the Partial Absorption Function, Penalty, and Reward 439 2.6.4 Mathematical Models of Penalty and Reward 442 2.6.5 Selecting Parameters of Partial Absorption 449 2.7 Logic Functions That Use Negation 453 2.7.1 Negation and De Morgan’s Duality 453 2.7.2 De Morgan’s Laws for Weighted Aggregators and Dualized Weighted Aggregators 455 2.7.3 De Morgan’s Duals of Compound Functions 458 2.7.4 Nonidempotent Logic Functions 460 2.8 Penalty-Controlled Missingness-Tolerant Aggregation 463 2.8.1 Missing Data in Evaluation Problems 463 2.8.2 Penalty-Controlled Numerical Coding of Missing Data 465 2.8.3 A Penalty-Controlled Missingness-Tolerant Aggregation Algorithm 467 2.8.4 The Impact of Penalty on Missingness-Tolerant Aggregation 472 2.9 Rating Scales and Verbalization 475 2.9.1 Design of Rating Scales 476 2.9.1.1 Strict Monotonicity of Linguistic Labeling 477 2.9.1.2 Linearity of Rating Scales 483 2.9.1.3 Balance of Rating Scales 486 2.9.1.4 Cardinality of Rating Scales 488 2.9.1.5 Hybrid Rating Scales 489 2.9.2 Stepwise Refinement of Rating Scales for Andness and Orness 491 2.9.3 Scaling and Verbalizing Degrees of Importance 496 2.9.4 Scaling and Verbalizing Degrees of Suitability/Preference 497 Part Three LSP METHOD 499 3.1 An Overview of the LSP Method 501 3.1.1 Characterization of Stakeholder and Organization of an Evaluation Project 503 3.1.2 Development of the Suitability Attribute Tree 506 3.1.3 Elementary Attribute Criteria 514 3.1.4 Logic Aggregation of Suitability 519 3.1.4.1 Logic Aggregation Using Graded Conjunction/ Disjunction 523 3.1.4.2 Logic Aggregation Using Partial Absorption 526 3.1.5 Cost/Suitability Analysis and Comparison of Evaluated Objects Using Their Overall Value 536 3.1.6 Summary of Properties of the LSP Method 540 3.2 LSP Decision Engineering Framework for Professional Evaluation Projects 543 3.2.1 Participants in a Professional Evaluation Process Based on LSP DEF 544 3.2.2 Relationships between Evaluators and Domain Experts 546 3.2.3 The Structure of LSP DEF and the Corresponding Professional Evaluation Process 547 3.2.4 Predictive Nature of Evaluation Models 551 3.2.5 Interpretation of Evaluation Results 552 3.2.6 Complexity, Completeness, and Accuracy of Evaluation Models 553 3.2.7 Combining Opinions of n Experts 555 3.2.7.1 The Maximum Likelihood Estimate 555 3.2.7.2 The Expert Competence Estimate 557 3.3 Elementary Attribute Criteria 561 3.3.1 Notation of Elementary Criteria 561 3.3.2 Verbalization of Elementary Criteria 565 3.3.3 Continuous Nonlinear Elementary Criteria 566 3.3.4 Classification of Twelve Characteristic Types of Elementary Criteria 569 3.4 Aggregation Techniques and Tools 579 3.4.1 Selecting GCD Aggregators for an LSP Project 579 3.4.2 Selecting GCD Aggregators by Training Preferential Neurons 581 3.4.3 Analytic Techniques for Selecting Partial Absorption Aggregators 589 3.4.3.1 AH Version of the Conjunctive Partial Absorption Aggregator 589 3.4.3.2 AH Version of the Disjunctive Partial Absorption Aggregator 594 3.4.4 Boundary Penalty/Reward Tables for Selecting Partial Absorption Aggregators 595 3.4.5 Selecting Partial Absorption Aggregators by Training Preferential Neurons 597 3.4.6 Nonstationary LSP Criteria 602 3.4.7 Graphic Notation of Aggregation Structures 606 3.5 Canonical Aggregation Structures 611 3.5.1 Conjunctive CAS with Increasing Andness 611 3.5.2 Disjunctive CAS with Increasing Orness 614 3.5.3 Aggregated Mandatory/Optional and Sufficient/Optional CAS 616 3.5.4 Design of a Simple LSP Evaluator Tool 617 3.5.5 Distributed Mandatory/Optional and Sufficient/Optional CAS 619 3.5.6 Nested Mandatory/Desired/Optional and Sufficient/Desired/Optional CAS 621 3.5.7 Decreasing Andness and Decreasing Orness CAS 622 3.6 Cost/Suitability Analysis as a Graded Logic Problem 623 3.6.1 Cost Analysis 623 3.6.2 Cost/Suitability Analysis Based on Linear Equi-Value Model 626 3.6.3 Using Cost/Suitability Analysis in Competitive Bidding 627 3.6.4 Conjunctive Suitability-Affordability Method 630 3.7 Sensitivity Analysis and Tradeoff Analysis 635 3.7.1 Sensitivity Analysis 635 3.7.1.1 Sensitivity with Respect to Input Suitability Scores 637 3.7.1.2 Sensitivity Properties of Basic Aggregators 641 3.7.1.3 Sensitivity with Respect to Input Attributes 643 3.7.2 Tradeoff Analysis 644 3.7.2.1 Compensatory Properties of LSP Criteria and Graded Logic Aggregators 647 3.7.2.2 The Concept of Compensation Ratio 651 3.8 Reliability Analysis 655 3.8.1 Sources of Errors in LSP Criteria and Their Empirical Analysis 655 3.8.2 The Problem of Confidence in Evaluation Results 660 3.8.3 Case Study of Reliability Analysis for a Computer Evaluation Project 664 3.9 System Optimization 671 3.9.1 Three Fundamental Constrained Optimization Problems 671 3.9.2 The Cloud Diagram and the Set of Optimum Configurations 673 3.9.3 A Case Study of Computer Configuration Optimization 675 3.10 LSP Software Technology 683 Part Four APPLICATIONS 689 4.1 Job Selection 693 4.1.1 Job Selection Attribute Tree 694 4.1.2 Elementary Attribute Criteria for Job Selection 697 4.1.3 Logic Aggregation of Suitability for the Job Selection Criterion 701 4.1.4 A Job Selection Example 705 4.2 Home Selection 711 4.2.1 Home Selection Using ORE Websites and LSPhome 711 4.2.2 Home Attribute Tree and Elementary Criteria 716 4.2.3 Home Suitability Aggregation Structure as a Shade Diagram 717 4.2.4 Using Missingness-Tolerant LSP Criteria 725 4.2.5 The Optimum Home Pricing Problem 728 4.2.6 A Personalized Home Selection Criterion 731 4.3 Evaluation of Medical Conditions 737 4.3.1 Evaluation of Disease Severity and Patient Disability 738 4.3.2 Limitations of Medical Rating Scales 740 4.3.3 LSP Models for Computing OSD, ODD, and PDD 743 4.3.4 Evaluation of PDD for Peripheral Neuropathy 745 4.3.5 The Risky Therapy Decision Problem 752 4.3.6 A Case Study of Anti-MAG Neuropathy 755 4.3.7 LSPmed—An Internet Tool for Medical Evaluation 758 4.3.7.1 LSPmed User Types and Their Functions 758 4.3.7.2 The Use of LSPmed 760 4.3.7.3 Serving a Patient 762 4.4 LSP Criteria in Ecology: Selecting Multi-Species Habitat Mitigation Projects 769 4.4.1 Multi-Species Compensatory Mitigation Projects 769 4.4.2 A Generic LSP Attribute Tree for Evaluation of Habitat Mitigation Projects 771 4.4.3 Attribute Criteria and the Logic Aggregation Structure 772 4.4.4 Sensitivity Analysis 777 4.4.5 Logic Refining of the Aggregation Structure 779 4.4.6 Cost/Suitability Analysis 781 4.4.7 MSHCP Software Support 783 4.5 Space Management Decision Problems 785 4.5.1 A Decision Model for School Location 785 4.5.1.1 Statement of the Problem 785 4.5.1.2 School Locations Attribute Tree 786 4.5.1.3 Elementary Criteria 786 4.5.1.4 Aggregation of Suitability Degrees 792 4.5.1.5 Cost Analysis 794 4.5.1.6 Competitive Locations 795 4.5.1.7 Cost/Suitability Analysis 796 4.5.2 Suitability of Locations for Residential Development 798 4.6 LSP Suitability Maps 803 4.6.1 The Concept of Map Logic and LSP Suitability Maps 803 4.6.2 Suitability Maps Based on Points of Interest 806 4.6.3 The Problem of Optimum Location of City Objects 810 4.6.4 Suitability Analysis of Urban Locations Using the LSPmap Tool 816 4.6.5 GIS-LSP Suitability Maps Based on TerrSet/Idrisi 821 4.6.6 GIS-LSP Suitability Maps Based on ArcGIS 823 4.7 Evaluation and Comparison of Search Engines 833 4.7.1 Search Engine User and Workload Models 834 4.7.2 SEben—A Search Engine Benchmarking Tool 837 4.7.3 LSP Criterion for Evaluation of Search Engines 838 4.7.4 Search Engine Evaluation Results 843 References 847 Index 871

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Book SynopsisThe first edition of Satellite Communications Systems Engineering (Wiley 2008) was written for those concerned with the design and performance of satellite communications systems employed in fixed point to point, broadcasting, mobile, radio navigation, data relay, computer communications, and related satellite based applications. This welcome Second Edition continues the basic premise and enhances the publication with the latest updated information and new technologies developed since the publication of the first edition. The book is based on graduate level satellite communications course material and has served as the primary text for electrical engineering Masters and Doctoral level courses in satellite communications and related areas. Introductory to advanced engineering level students in electrical, communications and wireless network courses, and electrical engineers, communications engineers, systems engineers, and wireless network engineers looking for a refresher wilTable of ContentsList of Acronyms xiii Preface to Second Edition xix 1 Introduction to Satellite Communications 1 1.1 Early History of Satellite Communications 3 1.1.1 SCORE 3 1.1.2 ECHO 3 1.1.3 COURIER 4 1.1.4 WESTFORD 4 1.1.5 TELSTAR 4 1.1.6 RELAY 4 1.1.7 SYNCOM 5 1.1.8 EARLYBIRD 5 1.1.9 APPLICATIONS TECHNOLOGY SATELLITE-1, ATS-1 5 1.1.10 ATS-3 5 1.1.11 ATS-5 6 1.1.12 ANIK A 6 1.1.13 ATS-6 6 1.1.14 CTS 8 1.2 Some Basic Communications Satellite System Definitions 9 1.2.1 Satellite Communications Segments 9 1.2.2 Satellite Link Parameters 10 1.2.3 Satellite Orbits 11 1.2.4 Frequency Band Designations 13 1.3 Overview of Book Structure and Topics 13 References 15 2 Satellite Orbits 17 2.1 Kepler’s Laws 18 2.2 Orbital Parameters 19 2.3 Orbits in Common Use 22 2.3.1 Geostationary Orbit 23 2.3.2 Low Earth Orbit 25 2.3.3 Medium Earth Orbit 26 2.3.4 Highly Elliptical Orbit 26 2.3.5 Polar Orbit 27 2.4 Geometry of GSO Links 27 2.4.1 Range to Satellite 29 2.4.2 Elevation Angle to Satellite 29 2.4.3 Azimuth Angle to Satellite 30 2.4.4 Sample Calculation 31 References 33 Problems 33 3 Satellite Subsystems 35 3.1 Satellite Bus 36 3.1.1 Physical Structure 37 3.1.2 Power Subsystem 38 3.1.3 Attitude Control 39 3.1.4 Orbital Control 39 3.1.5 Thermal Control 41 3.1.6 Electronic Propulsion Satellites 42 3.1.7 Tracking, Telemetry, Command, and Monitoring 43 3.2 Satellite Payload 45 3.2.1 Transponder 45 3.2.2 Antennas 47 References 48 4 The RF Link 49 4.1 Transmission Fundamentals 49 4.1.1 Effective Isotropic Radiated Power 51 4.1.2 Power Flux Density 51 4.1.3 Antenna Gain 52 4.1.4 Free-Space Path Loss 55 4.1.5 Basic Link Equation for Received Power 56 4.2 System Noise 59 4.2.1 Noise Figure 61 4.2.2 Noise Temperature 63 4.2.3 System Noise Temperature 66 4.2.4 Figure of Merit 69 4.3 Link Performance Parameters 70 4.3.1 Carrier-to-Noise Ratio 70 4.3.2 Carrier-to-Noise Density 72 4.3.3 Energy-per-Bit to Noise Density 72 Reference 73 Problems 73 5 Link System Performance 75 5.1 Link Considerations 75 5.1.1 Fixed Antenna Size Link 76 5.1.2 Fixed Antenna Gain Link 77 5.1.3 Fixed Antenna Gain, Fixed Antenna Size Link 77 5.2 Uplink 79 5.2.1 Multiple Carrier Operation 81 5.3 Downlink 81 5.4 Percent of Time Performance Specifications 82 References 84 Problems 85 6 Transmission Impairments 87 6.1 Radiowave Frequency and Space Communications 87 6.2 Radiowave Propagation Mechanisms 89 6.2.1 Absorption 90 6.2.2 Scattering 90 6.2.3 Refraction 90 6.2.4 Diffraction 90 6.2.5 Multipath 90 6.2.6 Scintillation 90 6.2.7 Fading 90 6.2.8 Frequency Dispersion 90 6.3 Propagation Below About 3 GHz 92 6.3.1 Ionospheric Scintillation 95 6.3.2 Polarization Rotation 97 6.3.3 Group Delay 98 6.3.4 Dispersion 99 6.4 Propagation Above About 3 GHz 100 6.4.1 Rain Attenuation 101 6.4.2 Gaseous Attenuation 105 6.4.3 Cloud and Fog Attenuation 107 6.4.4 Depolarization 108 6.4.5 Tropospheric Scintillation 114 6.5 Radio Noise 117 6.5.1 Specification of Radio Noise 119 6.5.2 Noise From Atmospheric Gases 121 6.5.3 Sky Noise Due To Rain 124 6.5.4 Sky Noise Due to Clouds 125 6.5.5 Noise From Extra-Terrestrial Sources 126 References 134 Problems 135 7 Propagation Effects Modeling and Prediction 138 7.1 Atmospheric Gases 138 7.1.1 Leibe Complex Refractivity Model 139 7.1.2 ITU-R Gaseous Attenuation Models 140 7.2 Clouds and Fog 152 7.2.1 ITU-R Cloud Attenuation Model 153 7.2.2 Slobin Cloud Model 155 7.3 Rain Attenuation 162 7.3.1 ITU-R Rain Attenuation Model 162 7.3.2 Crane Rain Attenuation Models 176 7.4 Depolarization 187 7.4.1 Rain Depolarization Modeling 188 7.4.2 Ice Depolarization Modeling 190 7.5 Tropospheric Scintillation 194 7.5.1 Karasawa Scintillation Model 194 7.5.2 ITU-R Scintillation Model 197 7.5.3 van de Camp Cloud Scintillation Model 199 References 201 Problems 203 8 Rain Fade Mitigation 205 8.1 Power Restoral Techniques 205 8.1.1 Beam Diversity 206 8.1.2 Power Control 207 8.1.3 Site Diversity 211 8.1.4 Orbit Diversity 227 8.2 Signal Modification Restoral Techniques 229 8.2.1 Frequency Diversity 230 8.2.2 Bandwidth Reduction 231 8.2.3 Time-Delayed Transmission Diversity 231 8.2.4 Adaptive Coding and Modulation 231 8.3 Summary 232 References 232 Problems 233 9 The Composite Link 235 9.1 Frequency Translation (FT) Satellite 236 9.1.1 Uplink 236 9.1.2 Downlink 238 9.1.3 Composite Carrier-to-Noise Ratio 238 9.1.4 Performance Implications 243 9.1.5 Path Losses and Link Performance 244 9.2 On-Board Processing (OBP) Satellite 248 9.2.1 OBP Uplink and Downlink 250 9.2.2 Composite OBP Performance 250 9.3 Comparison of FT and OBP Performance 252 9.4 Intermodulation Noise 255 9.5 Link Design Summary 257 References 258 Problems 258 10 Satellite Communications Signal Processing 261 10.1 Analog Systems 261 10.1.1 Analog Baseband Formatting 262 10.1.2 Analog Source Combining 264 10.1.3 Analog Modulation 264 10.2 Digital Baseband Formatting 270 10.2.1 PCM Bandwidth Requirements 273 10.2.2 Nearly Instantaneous Companding (NIC) 273 10.2.3 Adaptive Delta Modulation (ADM) or Continuously Variable Slope Delta Modulation (CVSD) 273 10.2.4 Adaptive Differential PCM (ADPCM) 274 10.3 Digital Source Combining 274 10.4 Digital Carrier Modulation 275 10.4.1 Binary Phase Shift Keying 278 10.4.2 Quadrature Phase Shift Keying 280 10.4.3 Higher Order Phase Modulation 283 10.5 Summary 283 Reference 284 Problems 284 11 Satellite Multiple Access 286 11.1 Frequency Division Multiple Access 289 11.1.1 PCM/TDM/PSK/FDMA 290 11.1.2 PCM/SCPC/PSK/FDMA 292 11.2 Time Division Multiple Access 293 11.2.1 PCM/TDM/PSK/TDMA 294 11.2.2 TDMA Frame Efficiency 295 11.2.3 TDMA Capacity 296 11.2.4 Satellite Switched TDMA 299 11.3 Code Division Multiple Access 303 11.3.1 Direct Sequence Spread Spectrum 306 11.3.2 Frequency Hopping Spread Spectrum 309 11.3.3 CDMA Processing Gain 310 11.3.4 CDMA Capacity 312 References 314 Problems 314 12 The Mobile Satellite Channel 316 12.1 Mobile Channel Propagation 316 12.1.1 Reflection 317 12.1.2 Diffraction 318 12.1.3 Scattering 318 12.2 Narrowband Channel 321 12.2.1 Path Loss Factor 323 12.2.2 Shadow Fading 327 12.2.3 Multipath Fading 333 12.2.4 Blockage 340 12.2.5 Mixed Propagation Conditions 346 12.3 Wideband Channel 348 12.4 Multi-Satellite Mobile Links 351 12.4.1 Uncorrelated Fading 351 12.4.2 Correlated Fading 353 References 355 13 Spectrum Management in Satellite Communications 357 13.1 Spectrum Management Functions and Activities 357 13.1.1 International Spectrum Management 358 13.1.2 World Radiocommunication Conference (WRC) 361 13.1.3 Frequency Allocation Process 361 13.1.4 Spectrum Management in the United States 365 13.2 Methods of Radio Spectrum Sharing 368 13.2.1 Frequency Separation 369 13.2.2 Spatial Separation 371 13.2.3 Time Separation 372 13.2.4 Signal Separation 372 13.3 Spectrum Efficiency Metrics 372 13.3.1 Spectrum Utilization Factor (U) 373 13.3.2 Spectrum Utilization Efficiency (SUE) 373 References 374 Problems 374 14 Interference Mitigation in Satellite Communications 376 14.1 Interference Designations 376 14.2 Modes of Interference for Satellite Services Networks 377 14.2.1 Interference Between Space and Terrestrial Services Systems 377 14.2.2 Interference Between Space Services Networks 378 14.2.3 Interference Between Space Services Networks with Reverse Band Allocations 379 14.3 Interference Propagation Mechanisms 379 14.3.1 Line-of-Sight Interference 381 14.3.2 Diffraction 382 14.3.3 Tropospheric Scatter 383 14.3.4 Surface Ducting and Layer Reflection 383 14.3.5 Hydrometeor (Rain) Scatter 384 14.4 Interference and the RF Link 386 14.4.1 Single Interferer (pfd) 387 14.4.2 Multiple Interferers (epfd) 387 14.5 Coordination for Interference Mitigation 388 14.5.1 Radio-Climate Zones 390 14.5.2 Distance Limits 391 14.5.3 Coordination Distance for Mode (1) Propagation 392 14.5.4 Coordination Distance for Mode (2) Propagation 393 14.5.5 ITU-R Coordination Procedures for Satellite and Terrestrial Services 394 References 395 Problems 396 15 High Throughput Satellites 398 15.1 Evolution of Satellite Broadband 399 15.2 Multiple Beam Antennas and Frequency Reuse 401 15.2.1 Multiple Beam Antenna Array Design 402 15.2.2 Adjacent Beam SIR 406 15.3 HTS Ground Systems Infrastructure 412 15.3.1 Network Architectures 412 15.3.2 Frequency Band Options 413 15.4 Satellite HTS and 5G 416 15.4.1 Cellular Mobile Technology Development 416 15.4.2 Satellite 5G Technologies 418 References 422 Appendix Error Functions and Bit Error Rate 423 A.1 Error Functions 423 A.2 Approximation for BER 425 Index 427

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Book SynopsisI was pleased to review Dan''s new book - pleased because he addresses an old topic in a new way. He is making no assumptions for trainers who are not fully experienced andseasoned. Hetakes them step-by-step through practical and realistic methods to set up training graduatesto actually be on-the-job performers. Enjoy,learn and be inspired. Jim Kirkpatrick, PhD Senior Consultant, Kirkpatrick Partners, USA Daniel Bixby's approach to Product Training for technical experts is practical, relevant and exactly what anyone who is required to train others on technical content really needs. He writes with candor and with a sense of ease, making the reader feel as though he is right there with you helping to develop your training competency. A must read for anyone on your team required to provide technical training to others! Jennifer Alfaro Chief Human Resources Officer, USA An expert guide to developinTable of ContentsForeword xix Preface xxi Acknowledgments xxiii How to Use This Book xxv About the Companion Website xxix Introduction xxxi Part I The Foundation of Hands-On Learning 1 1 Hands-On Learning in the Classroom: Articulate Your Approach 3 Product Training as You Know It 3 What Makes Training Effective? 4 Your Goal: Proficiency 6 Articulating Your Training Approach 6 Three Things to Document 7 Adult Learning Principles: The Foundation of Hands-On Learning 8 The Strategy of Hands-On Learning 10 The Structure of Hands-On Learning 10 The Delivery of Hands-On Learning 10 Conclusion 11 Making It Practical 11 Notes 12 2 Experiencing Learning: Emphasize Skill over Information 13 How Does One Develop a Skill? 13 Remember How You Became an Expert 14 Build on Your Students’ Experiences 14 Create Experiences in the Classroom 15 Let Them Learn from Negative Experiences 16 Allow Students to Make Mistakes 17 Capitalize on Informal Learning 17 Allow Students to Share Their Experiences 18 Give Lecture and Observation Their Rightful Place 19 Provide a Structure for Your Hands-On Training 19 Phase One: Exhibit the Product 19 Phase Two: Execute a Function 20 Phase Three: Explore Independently 20 Apply All Three Phases 21 Conclusion 21 Making It Practical 21 Note 22 3 You Know It, Can You Teach It? Overcoming Your Own Intelligence 23 Address Your Biggest Challenge: Yourself 23 The Four Stages of Competency Applied to Instructors 24 Unconsciously Unskilled 25 Consciously Unskilled 25 Consciously Skilled 25 Unconsciously Skilled 25 Why Experts Find It Difficult to Teach 26 Experts Rarely Remember How They Perfected Their Skill 26 Experts Have Trouble Distinguishing Between the Simple and the Difficult 26 Experts Don’t Differentiate Between the Essential and the Nonessential 27 How Experts Can Teach It 27 Ask the Instructor (Yourself) the Right Questions 28 Conclusion 29 Making It Practical 29 Note 30 4 Ready or Not? Why Some Students Are More Ready to Learn Than Others 31 The Four Principles of Learner-Readiness 31 They Must Recognize the Need for Learning 32 What if Their Reason for Learning Is Wrong? 32 They Must Take Responsibility for Their Learning 32 Questions Demonstrate Learning 33 The Instructor’s Responsibility 33 They Must Relate It to Their Experience 34 They Must Be Ready to Apply It 35 Conclusion 35 Making It Practical 36 Part II The Strategy of Hands-On Learning 37 5 It is Never Just Product Training: Why You Should Offer the Training 39 Product Solution Training Versus Talent Development 39 Employee Product Training 40 Customer Product Training 41 Business Plan 41 Training as a Cost of Doing Business 41 Training as a Profit Center 42 Training that Sells Products 44 Conclusion 44 Making It Practical 45 Note 46 6 From Good to Great: Defining the Focus of Effective Product Training 47 Aim at the Right Target: Doing Versus Knowing 47 Change the Approach: Facilitator Versus Lecturer 48 Call It the Right Thing: Training Versus Presentation 49 Make It Sustainable: Standardized Versus Customized 51 Measure the Right Things: Performance Versus Reactions 51 Value the Right Things: Results Versus Head Count 52 Use the Right Delivery Methods: Effectiveness Versus Availability 52 Continue the Conversation: Process Versus Event 54 Keep Improving: Progress Versus Contentment 55 Conclusion 55 Making It Practical 55 7 What Is Expected Must Be Inspected: Assessing and Evaluating Hands-On Learning 57 Assessing the Individual 58 Assessing Their Knowledge 58 Quizzes 58 Exams 59 About Creating Exam Questions 59 About Administrating the Exam 60 Assessing Their Skills 60 Creative Assessments 61 Combining the Grades 61 Evaluating the Class 62 Evaluating Perceptions 64 A Note about Measuring Instructor’s Facilitation Skills 65 Conclusion 65 Making It Practical 65 Notes 66 Part III The Structure of Hands-On Learning 67 8 Dethroning King Content: A Paradigm Shift 69 When Content Is King 70 What if Content Is All They Need? 70 How to Tell if Content Is King 71 Giving Content Its Rightful Place 71 Introducing the 4 × 8 Proficiency Design Model 72 Is Training the Solution? 73 Training Will Not Improve Your Product or Solution 74 Training Is Not a Marketing Gimmick 74 How Can You Know if Training Is the Solution? 75 Conclusion 75 Making It Practical 76 Note 77 9 Designing for Proficiency: Determining the Curriculum 79 The 4 × 8 Proficiency Design Model 80 Level 1 80 Business Goal 80 Intended Audience 81 Level 2 82 Objectives 82 Exercise 83 Level 3 84 Outline 84 Constructive Activities 87 Determine Delivery Method 88 Delivery Method 88 Duration 89 Maximum Number of Students 89 Other Logistics 89 Level 4 89 Provide an Assessment to Validate the Learning 89 Create the Content 89 Why Is Content After Assessment? 90 Conclusion 90 Making It Practical 91 10 Pixels or Paper? How to Build the Content and Deliverables 93 Ask the Questions Again 93 Create a Student Guide 94 Create Your Visual Aids 95 Creating Presentation Slides 96 Use the Software Correctly 96 Don’t Rely on a Presentation 96 Don’t Let the Presentation Tie You Down 97 Know Your Material 97 Creating Handouts 98 Statement of Indemnification 98 Create an Instructor’s Guide 99 Running a Pilot Class 99 When an Instructor Teaches This Class for the First Time 99 When This Class Is Being Taught for the First Time 100 Handpick the Audience 100 Plan on Extra Time 100 Be Aware of Too Many Auditors 100 Debrief with Everyone 101 Debrief with Your Core Team 101 Conclusion 101 Making It Practical 101 Part IV The Facilitation of Hands-On Learning 103 11 Speak Up: Effective Verbal Engagement 105 Decorative Speaking 106 Controlled Energy 106 Controlled Breathing 106 Controlled Pitch 107 Controlled Tempo 108 Controlled Volume 108 Controlled Articulation 109 Declarative Speaking 109 Controlled Jargon 109 Verbal Crutches 110 If Your Use of Verbal Crutches Is a Communication Issue 110 If Your Use of Verbal Crutches Is a Habit 111 Poor Grammar 111 Conclusion 111 Making It Practical 112 Notes 113 12 Shut Up: Effective Listening and Engagement 115 What You Are Listening for 115 What They Already Know (or Think They Know) 116 What They Want to Learn 116 What They Have Learned 117 The Foundation for Engaging Learning 117 Students Learn Better When They’re Awake 117 Learners Require Time to Absorb the Learning 117 Set the Expectation for Engagement 118 Practical Engagement in the Classroom 118 Engaging as a Conversation 118 Engaging with Questions and Answers 120 Why Instructors Ask Questions 120 When and How to Ask Questions 121 Answering Student Questions 122 Engaging Group Learning Activities 123 Engaging Labs and Exercises 124 Icebreakers, Games, and Other Interactive Options 124 When Should They Be Done? 125 Games and Gamification 125 Interactive Technology 126 Conclusion 126 Making It Practical 126 13 Stand Up: Effective Nonverbal Engagement 129 Observed Communication: What They See You Saying 129 Posture 130 Facial Expressions 131 Eye Contact 131 Gestures 132 Physical Presence 132 Physical Appearance 133 Perceived Communication: What They Feel You Are Saying 134 Be Genuine and Humble 134 Be Likeable and Pleasant 134 Be Available and Prepared 134 Be Positive and Have Fun 134 Be Confident and in Control 135 Environmental Influences 136 Room Layout 136 Furniture, Lighting, and Technology 136 Know Your Environment 136 Hosting a Training Event 137 Make Your Students Feel Welcome 137 Conclusion 138 Making It Practical 139 Note 140 14 The Smartest Engineer: And Other Difficult Students 141 Set the Expectations at the Beginning 141 Take Responsibility for Your Learning 141 Be Prepared for Difficult Responses 142 The Stubborn Mule 142 The Pessimist 143 The Helper 143 The Talker 144 The Extreme Introvert 144 The Sleeper 144 The Expert 145 Conclusion 145 Making It Practical 146 15 Virtual Facilitation: Tips for Effective Webinars 147 What Doesn’t Change 147 The Philosophical Approach 147 The Structure 148 The Definition 148 Facilitating Virtually 148 Regarding the Presentation 149 Regarding the Tool 149 About the Event 149 Conclusion 150 Making It Practical 150 16 Technical Presentations: Effectively Design and Deliver Technical Information 151 When to Use Presentations 151 When the Objective Is to Deliver Information 152 When Time Is Limited 152 When the Audience Is Large 153 To Motivate and Encourage Change 154 How to Design Effective Technical Presentations 154 Determine the Delivery Method (Optional) 156 Informational Objectives 156 Motivational Objectives 156 Delivering Your Presentation 159 Ask Questions 159 Practice, Practice, Practice 159 Relax and Have Fun! 160 Conclusion 160 Making It Practical 160 17 Culture and Proficiency: Training for Proficiency in a Global Environment 161 What Doesn’t Change 162 The Philosophy of Hands-on Learning 162 The Strategy of Hands-on Learning 162 The Structural Design of Hands-on Learning 163 What Does Change 163 The Delivery of Hands-on Learning 163 The Facilitation of Hands-on Learning 164 Other Tips for the Traveling Trainer 165 Conclusion 165 Making It Practical 166 Part V The Operation of Hands-On Learning 167 18 Certifying Proficiency: The Fundamentals of a Product Proficiency Certification Program 169 What Is Product Proficiency Certification? 169 When Do You Need a Certification Program? 170 When Is a Certificate Program Sufficient? 170 Why You Should Consider a Certification Program 171 If the Product Is Complex 171 If Your Product Is Unique 172 Products That Are New to the Market 172 When the Go-to-Market Strategy Is Indirect or Complex 172 If It Involves More Than One Party to Integrate 173 If There Are Standards That Must Be Met 174 If There Are Industry or Company Standards That Must Be Met 174 When Quality Standards Must Be Verified 174 If the Product or Technology Changes Regularly 175 If Misuse Could Cause a Safety Issue 175 The Requirements of Product Proficiency Certification 175 Proof of Authenticity 176 Board of Decision-Makers 176 Curriculum and Program Acceptance 176 Proof of Conformity 176 Education or Experience 177 Exam and/or Proficiency Assessment 177 Code of Conduct 177 Recertification or Maintenance 177 Instructor Certification Process 178 Proof of Impartiality 179 Selection and Opportunity 179 Administration and Traceability 179 Exceptions and Deviations 179 Documenting the Certification Program 180 Certification Program Document 180 Process Documents 180 Conclusion 182 Making It Practical 182 Notes 182 19 Managing the Details: The Effective Administration of Hands-On Learning 183 Measurability 183 Sustainability 184 Revision Control 185 Simple Revision Tracking 185 Global Enterprise Classification 186 Propose, Approve, Implement 191 Train the Trainer 191 Prerequisites and Follow-Up 192 Prerequisites 192 Follow-Up 192 Traceable 193 Tracking People and Programs 193 Tracking Business Results 195 Tracking Compliance 196 Tracking Revenue Generation 196 Tracking Cost Savings 196 Improve Services 196 Conclusion 197 Making It Practical 197 Notes 197 20 Developing New Product Talent: Effective Mentoring of New and Junior Employees 199 Why Mentoring Matters 199 Why It Matters to the Mentor 200 Employers Value Mentoring Experts 200 Successful Experts Are Teaching Experts 201 Why It Matters to Your Company 201 Mentored Employees Have Real Input Sooner 201 More Meaningful Experience Sooner 202 Mentoring for Proficiency 202 Multiple Mentors 202 Real-Time Mentoring 203 Partnership Mentoring 203 The Foundation of a Mentoring Program 203 Develop a Structure for Success 203 Get Appropriate Endorsement and Approvals 204 Set Realistic Goals 204 Create Individual Objectives 204 Define the Qualifications of a Good Mentor 205 Aptitude 205 Attitude 205 Conclusion 206 Making It Practical 206 21 Now, Go Do It: To Be an Effective Trainer, You Must Train 207 Define Your Approach 207 DO Articulate How You Will Make Learning Effective 207 DO Emphasize Proficiency over Knowledge 207 DO Become Consciously Skilled on Your Products 208 DO Identify Students That Are Ready to Learn 208 Develop with a Strategy 208 DO Demonstrate the Value of Training 208 DO Improve Your Training from Good to Great 208 DO Inspect and Evaluate Your Training 208 Design with a Structure 208 DO Dethrone King Content 208 DO Use the 4 × 8 Proficiency Design Model 209 DO Build Engaging Content and Deliverables 209 Deliver with a Purpose 209 DO Speak Up 209 DO Shut Up and Listen to Your Students 209 DO Stand Up and Be Confident 209 DO Prepare for Difficult Students and Circumstances 209 DO Deliver Effective Virtual Training 209 DO Deliver Effective Technical Presentations 210 DO Allow for Flexibility When Training in Other Cultures 210 Don’t Forget the Details 210 DO Define Certification Properly 210 DO Manage the Details Properly 210 DO Mentor New Employees 210 Conclusion 210 Making It Practical 211 Part VI For the Boss: Executive Overviews 213 22 The Foundation of Hands-On Learning: An Executive Summary 215 An Overview 215 How You Can Help 216 Conclusion 217 23 The Strategy of Hands-On Learning: An Executive Summary 219 Overview 219 How You Can Help 220 Conclusion 221 24 The Structure of Hands-On Learning: An Executive Summary 223 Overview 223 How You Can Help 224 Conclusion 225 25 The Facilitation of Hands-On Learning: An Executive Summary 227 Overview 227 How You Can Help 228 Conclusion 229 26 The Operation of Hands-On Learning: An Executive Summary 231 Overview 231 How You Can Help 232 Conclusion 233 Index 235

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Book SynopsisThis comprehensive text examines existing and emerging electrical drive technologies. The authors clearly define the most basic electrical drive concepts and go on to explain the most important details while maintaining a solid connection to the theory and design of the associated electrical machines. Also including links to a number of industrial applications, the authors take their investigation of electrical drives beyond theory to examine a number of practical aspects of electrical drive control and application. Key features: * Provides a comprehensive summary of all aspects of controlled-speed electrical drive technology including control and operation. * Handling of electrical drives is solidly linked to the theory and design of the associated electrical machines. Added insight into problems and functions are illustrated with clearly understandable figures. * Offers an understanding of the main phenomena associated with electrical mTable of ContentsPreface vii Abbreviations and Symbols ix 1 Introduction to Electrical Machine Drives Control 1 2 Aspects Common to All Controlled Electrical Machine Drive Types 17 3 The Fundamentals of Electric Machines 36 4 The Fundamentals of Space-Vector Theory 66 5 Torque and Force Production and Power 91 6 Basic Control Principles for Electric Machines 107 7 DC and AC Power Electronic Topologies – Modulation for the Control of Rotating-Field Motors 147 8 Synchronous Electrical Machine Drives 191 9 Permanent Magnet Synchronous Machine Drives 296 10 Synchronous Reluctance Machine Drives 346 11 Asynchronous Electrical Machine Drives 373 12 Switched Reluctance Machine Drives 449 13 Other Considerations: The Motor Cable, Voltage Stresses, and Bearing Currents 469 Index 499

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Book SynopsisProvides a detailed analysis of the standards and technologies enabling applications for the wireless Internet of Things The Wireless Internet of Things: A Guide to the Lower Layers presents a practitioner's perspective toward the Internet of Things (IoT) focusing on over-the-air interfaces used by applications such as home automation, sensor networks, smart grid, and healthcare. The authora noted expert in the fieldexamines IoT as a protocol-stack detailing the physical layer of the wireless links, as both a radio and a modem, and the media access control (MAC) that enables communication in congested bands. Focusing on low-power wireless personal area networks (WPANs) the text outlines the physical and MAC layer standards used by ZigBee, Bluetooth LE, Z-Wave, and Thread. The text deconstructs these standards and provides background including relevant communication theory, modulation schemes, and access methods. The author includes a discussion on Wi-Fi aTable of ContentsPreface vii Acknowledgments ix About the Author xi 1 Introduction 1 1.1 What is the Internet of Things? 1 1.2 What is the Wireless Internet of Things? 4 1.3 Wireless Networks 5 1.4 What is the Role of Wireless Standards in the Internet of Things? 10 1.5 Protocol Stacks 10 1.6 Introduction to the Protocols for the Wireless Internet of Things 16 1.7 The Approach of this Book 17 References 18 2 Protocols of the Wireless Internet of Things 21 2.1 Bluetooth 22 2.2 ITU G.9959 29 2.3 Z-Wave 32 2.4 IEEE 802.15.4 33 2.5 The ZigBee Specification 38 2.6 Thread 40 2.7 Wi-Fi 41 References 44 3 Radio Layer 47 3.1 The Wireless System 47 3.2 Basic Transceiver Model 48 3.3 The Basics of Channels 67 3.4 Bit and Symbol Error Rate 74 3.5 Complex Channels 76 References 81 4 Modem Layer 83 4.1 The Signal Model 84 4.2 Pulse Shaping 90 4.3 Modulation Techniques 95 4.4 Synchronization 120 4.5 Spread Spectrum 132 References 137 5 MAC Layer 139 5.1 Bands and Spectrum Planning 140 5.2 Spectrum Access for the Wireless IoT 144 5.3 Multiple Access Techniques 145 5.4 Spread Spectrum as Multiple Access 153 5.5 Error Detection and Correction 154 5.6 Energy Efficiency 167 References 170 6 Conclusion 173 6.1 Selecting the Right Standard 173 6.2 Higher Layer Standardization and the Future of IoT 175 Index 177

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Book SynopsisA professional guide to the fundamentals of power integrity analysis with an emphasis on silicon level power integrity Power Integrity for Electrical and Computer Engineers embraces the most recent changes in the field, offers a comprehensive introduction to the discipline of power integrity, and provides an overview of the fundamental principles. Written by noted experts on the topic, the book goes beyond most other resources to focus on the detailed aspects of silicon and optimization techniques in order to broaden the field of study. This important book offers coverage of a wide range of topics including signal analysis, EM concepts for PI, frequency domain analysis for PI, numerical methods (overview) for PI, and silicon device PI modeling.Power Integrity for Electrical and Computer Engineers examine platform technologies, system considerations,power conversion, system level modeling, and optimization methodologies. To reinforce the material presented, the authors include examplTable of ContentsPart I Power Integrity Fundamentals 1 1 Introduction 3 1.1 Introduction to Power Integrity for Computer Engineers 3 1.2 Some Advancements in Power Integrity 5 1.3 First Principles Analysis 10 1.4 Scope of Text 15 Bibliography 19 2 Power Conversion for Power Integrity 21 2.1 Power Distribution Systems 21 2.2 The Buck Converter 27 2.2.1 The LC Filter 30 2.2.2 Silicon Power Devices in a Buck Regulator 37 2.2.2.1 Power MOSFETs 37 2.3 Inductors 53 2.3.1 Losses in Power Inductors 60 2.4 Controllers 69 2.4.1 A Simple Feedback System 71 2.4.2 Generalized Controller Feedback Design Setup 74 2.4.3 Buck Regulator Design Example 76 2.5 Integration of Closed Loop Model into SPICE 82 2.6 Short Discussion on System Considerations for Power Conversion Integration 90 2.7 Advanced Topics in Power Conversion 91 2.8 Summary 97 Bibliography 102 3 Platform Technologies and System Considerations 105 3.1 Physical Elements 106 3.1.1 Capacitors for PDN Applications 121 3.2 Power Delivery System Interaction 130 3.2.1 Power Load Line Fundamentals 130 3.2.1.1 Tolerance Band 139 3.2.1.2 Voltage Guardband 143 3.3 System Noise Considerations in Power Integrity 150 3.4 EMI and Power Integrity 154 3.5 Brief Discussion on Noise Mitigation for Power Integrity 161 3.6 Summary 162 Bibliography 164 4 Electromagnetic Concepts for Power Integrity 167 4.1 Coordinate Systems 169 4.1.1 The Cylindrical Coordinate System 172 4.1.2 The Spherical Coordinate Systems 175 4.2 EM Concepts – Maxwell’s Equations 177 4.2.1 The Biot–Savart Law 182 4.2.2 The Magnetic Vector Potential 186 4.3 Some Useful Closed-Form Equations 188 4.3.1 Simple Plane-Pair Inductance 190 4.3.2 Inductance of Two Wires in Space 192 4.3.3 Resistance Between Two Vias in a Plane 193 4.3.4 Inductance of Small Wire or Trace Above Plane Using Image Theory 196 4.4 Examples of Using Equations 197 4.4.1 Power Trace Above a Plane Between Capacitors 197 4.4.2 Inductance of a Trace Over a Plane 199 4.5 Summary 201 Bibliography 203 Part II Tools for Power Integrity Analysis 205 5 Transmission Line Theory and Application 207 5.1 Telegrapher’s Equations 207 5.1.1 Damped Transmission Line Approximation 209 5.2 Frequency-Domain Analysis Fundamentals 211 5.3 Power Planes, Grids, and Transmission Lines 224 5.4 Summary 226 Bibliography 227 6 Signal Analysis Review 229 6.1 Linear, Time-Invariant Systems 229 6.2 The Dirac Delta Function 230 6.3 Convolution 231 6.4 Fourier Series 234 6.5 Fourier Transform 239 6.5.1 Convolution Theorem 240 6.5.2 Time-Shift Theorem 241 6.5.3 Superposition Theorem 241 6.5.4 Duality Theorem 242 6.5.5 Differentiation Theorem 242 6.5.6 Integration Theorem 242 6.5.7 Multiplication Theorem 245 6.5.8 Time-Scaling Theorem 245 6.5.9 Modulation or Frequency-Translation Theorem 246 6.6 Laplace Transform 250 6.6.1 Convolution Theorem 251 6.6.2 Time-Shift Theorem 251 6.6.3 Superposition Theorem 252 6.6.4 Differentiation Theorem 252 6.6.5 Integration Theorem 253 6.6.6 Multiplication Theorem 254 6.6.7 S-shift Theorem 254 6.7 Summary 261 Bibliography 262 7 Numerical Methods for Power Integrity 263 7.1 Introduction to Analytical Methods 266 7.1.1 Separation of Variables 267 7.1.2 Introduction to Variational Methods 278 7.1.2.1 The Galerkin Method 285 7.1.3 Conformal Mapping 288 7.2 Numerical Methods 292 7.2.1 The Finite Difference Method 292 7.2.2 The Finite Element Method 311 7.3 Error and Convergence 315 7.3.1 Errors in Numerical Analysis 316 7.3.2 Convergence and Accuracy 319 7.4 Summary 321 Bibliography 323 Part III Power Integrity Analytics 327 8 Frequency-Domain Analysis 329 8.1 Introduction to FDA 329 8.2 The PDN Structure, Physically and Electrically 331 8.2.1 The Damped Transmission Line Approximation 333 8.2.2 The Subcomponents of the PDN 343 8.3 Analytical Methods 350 8.4 Excitation in PDN Systems 364 8.5 PDN Optimization 376 8.5.1 Monte Carlo Analysis 383 8.6 Power Loss in PDN Systems 388 8.7 Summary 390 Bibliography 392 9 Time-Domain Analysis 395 9.1 Introduction to TDA 395 9.1.1 Data and Power Integrity 396 9.2 Voltage Droop Definitions 398 9.3 Droop Behavior and Dynamic Loads 399 9.3.1 Step Response 403 9.3.2 High-Frequency Pulse Droop 408 9.3.3 Susceptible State Voltage Droop 421 9.4 Analytical Approach to Step Response 430 9.5 Boundary Budget System Discussion 436 9.6 Power Loss Due to the PDN 439 9.6.1 Dynamic Silicon Power and Leakage 440 9.6.2 DC Losses in the PDN 446 9.6.3 AC Power Loss in PDN 451 9.7 Summary 454 Bibliography 458 10 Silicon Power Integrity 461 10.1 Introduction 461 10.2 Device Construction and Architecture Considerations 463 10.3 On-die Decoupling 476 10.4 Device Metal Routing Revisited 483 10.5 The Localized Impedance Network 490 10.6 Multi-rail vs. Single Rail Power Discussion 494 10.7 On-die Gating 499 10.8 Discussion of System-Level Issues with Charge and Current Density 502 10.9 Noise 507 10.10 Summary 516 Bibliography 520 Appendices 523 A.1 Introduction to SPICE 523 A.1.1 The SPICE Deck 524 A.1.2 Sources and Loads 526 A.1.3 Passive Elements 529 A.1.4 Transistor Formats 531 A.1.5 Analysis Calls, Frequency/Time Steps, and Initial Conditions 532 A.1.6 Some SPICE Examples 533 B.1 Quasi-Static Fields 537 C.1 Spherical Coordinate System 540 D.1 Vector Identities and Formula 541 E.1 Summary of Common Relationships Among Coordinate Systems 542 E.1.1 Variable Translations 542 E.1.2 Coordinate Translations 543 E.1.3 Curl Equation Expansions 544 E.1.4 Divergence Equation Expansions 544 E.1.5 Del-Operator Expansions 544 E.1.6 Laplacian Expansions 545 F.1 Some Notation Definitions 545 G.1 Common Theorems 546 Bibliography 546 Index 547

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Book SynopsisAn up-to-date, comprehensive guide for advanced electrical engineering studentsand electrical engineers working in the IC and optical industries This book covers the major transimpedance amplifier (TIA) topologies and their circuit implementations for optical receivers.Table of ContentsPreface vii References xi 1 Introduction 1 1.1 Optical Transceivers 1 1.2 Modulation Formats 5 1.3 Transmission Modes 12 References 20 2 Optical Fibers 25 2.1 Loss and Bandwidth 25 2.2 Dispersion 29 2.3 Nonlinearities 34 2.4 Pulse Spreading due to Chromatic Dispersion 37 2.5 Summary 40 Problems 41 References 42 3 Photodetectors 45 3.1 pin Photodetector 46 3.2 Avalanche Photodetector 60 3.3 pin Detector with Optical Preamplifier 67 3.4 Integrated Photodetectors 78 3.5 Detectors for Phase-Modulated Optical Signals 86 3.6 Summary 94 Problems 96 References 97 4 Receiver Fundamentals 107 4.1 Receiver Model 108 4.2 Noise and Bit-Error Rate 110 4.3 Signal-to-Noise Ratio 116 4.4 Sensitivity 120 4.5 Noise Bandwidths and Personick Integrals 134 4.6 Optical Signal-to-Noise Ratio 138 4.7 Power Penalty 146 4.8 Inter-symbol Interference and Bandwidth 151 4.9 Frequency Response 162 4.10 Summary 167 Problems 168 References 171 5 Transimpedance Amplifier Specifications 177 5.1 Transimpedance 177 5.2 Input Overload Current 182 5.3 Maximum Input Current for Linear Operation 183 5.4 Bandwidth 184 5.5 Phase Linearity and Group Delay Variation 186 5.6 Timing Jitter 187 5.7 Input Referred Noise Current 187 5.8 Crosstalk 193 5.9 Product Examples 195 5.10 Summary 195 Problems 197 References 198 6 Basic Transimpedance Amplifier Design 201 6.1 Low and High Impedance Front Ends 202 6.2 Shunt Feedback TIA 205 6.3 Noise Analysis 224 6.4 Noise Optimization 236 6.5 Noise Matching 248 6.6 Summary 260 Problems 262 References 265 7 Advanced Transimpedance Amplifier Design I 271 7.1 TIA with Post Amplifier 271 7.2 TIA with Differential Inputs and Outputs 276 7.3 TIA with DC Input Current Control 281 7.4 TIA with Adaptive Transimpedance 284 7.5 Common Base and Common Gate TIAs 292 7.6 Regulated Cascode TIA 303 7.7 TIA with Inductive Broadbanding 311 7.8 Distributed Amplifier TIA 315 7.9 Summary 321 Problems 323 References 324 8 Advanced Transimpedance Amplifier Design II 331 8.1 TIA with Nonresistive Feedback 331 8.2 Current Mode TIA 337 8.3 TIA with Bootstrapped Photodetector 339 8.4 Burst Mode TIA 340 8.5 Analog Receiver TIA 347 8.6 Summary 351 Problems 352 References 352 9 Transimpedance Amplifier Circuit Examples 359 9.1 BJT, HBT, and BiCMOS Circuits 359 9.2 CMOS Circuits 366 9.3 MESFET and HFET Circuits 373 9.4 Summary 375 References 378 A Communication Signals 383 A.1 NonReturn-to-Zero Signal 384 A.2 Return-to-Zero Signal 387 A.3 Pulse Amplitude Modulated Signal 389 A.4 Analog Television Signal 391 A.5 Digital Television Signal 394 References 396 B Eye Diagrams 397 References 404 C Timing Jitter 405 C.1 Data Jitter 405 C.2 Clock Jitter 415 C.3 Jitter, Phase Noise, and BitError Rate 419 Problems 422 References 422 D Nonlinearity 425 D.1 Gain Compression 426 D.2 Harmonic Distortions 427 D.3 Intermodulation Distortions 429 D.4 Composite Distortions 430 Problems 433 References 433 E Adaptive Equalizers 435 E.1 Feedforward and Decision Feedback Equalizers 436 E.2 Adaptation Algorithms 440 E.3 Hardware Implementations 444 Problems 447 References 447 F Decision Point Control 453 Problems 457 References 457 G Forward Error Correction 459 Problems 464 References 465 H Second Order Low Pass Transfer Functions 467 References 479 I Answers to the Problems 481 References 514 J Notation 517 K Symbols 519 L Acronyms 529 Index 537

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Book SynopsisRF/MICROWAVE ENGINEERING AND APPLICATIONS IN ENERGY SYSTEMS An essential text with a unique focus on RF and microwave engineering theory and its applications In RF/Microwave Engineering and Applications in Energy Systems, accomplished researcher Abdullah Eroglu delivers a detailed treatment of key theoretical aspects of radio-frequency and microwave engineering concepts along with parallel presentations of their practical applications. The text includes coverage of recent advances in the subject, including energy harvesting methods, RFID antenna designs, HVAC system controls, and smart grids. The distinguished author provides step-by-step solutions to common engineering problems by way of numerous examples and offers end-of-chapter problems and solutions on each topic. These practical applications of theoretical subjects aid the reader with retention and recall and demonstrate a solid connection between theory and practice. The author also applies common simulation tools in several cTable of ContentsPreface xiii Biography xv Acknowledgments xvii About the Companion Website xix 1 Fundamentals of Electromagnetics 1 1.1 Introduction 1 1.2 Line, Surface, and Volume Integrals 1 1.2.1 Vector Analysis 1 1.2.1.1 Unit Vector Relationship 1 1.2.1.2 Vector Operations and Properties 2 1.2.2 Coordinate Systems 4 1.2.2.1 Cartesian Coordinate System 4 1.2.2.2 Cylindrical Coordinate System 5 1.2.2.3 Spherical Coordinate System 6 1.2.3 Differential Length (dl), Differential Area (ds), and Differential Volume (dv) 8 1.2.3.1 dl, ds, and dv in a Cartesian Coordinate System 8 1.2.3.2 dl, ds, and dv in a Cylindrical Coordinate System 8 1.2.3.3 dl, ds, and dv in a Spherical Coordinate System 9 1.2.4 Line Integral 10 1.2.5 Surface Integral 12 1.2.6 Volume Integral 12 1.3 Vector Operators and Theorems 13 1.3.1 Del Operator 13 1.3.2 Gradient 13 1.3.3 Divergence 15 1.3.4 Curl 16 1.3.5 Divergence Theorem 16 1.3.6 Stokes’ Theorem 19 1.4 Maxwell’s Equations 21 1.4.1 Differential Forms of Maxwell’s Equations 21 1.4.2 Integral Forms of Maxwell’s Equations 22 1.5 Time Harmonic Fields 23 References 25 Problems 25 2 Passive and Active Components 27 2.1 Introduction 27 2.2 Resistors 27 2.3 Capacitors 29 2.4 Inductors 32 2.4.1 Air Core Inductor Design 34 2.4.2 Magnetic Core Inductor Design 36 2.4.3 Planar Inductor Design 37 2.4.4 Transformers 38 2.5 Semiconductor Materials and Active Devices 39 2.5.1 Si 40 2.5.2 Wide-Bandgap Devices 40 2.5.2.1 GaAs 41 2.5.2.2 GaN 41 2.5.3 Active Devices 41 2.5.3.1 BJT and HBTs 41 2.5.3.2 FETs 43 2.5.3.3 MOSFETs 44 2.5.3.4 LDMOS 53 2.5.3.5 High Electron Mobility Transistor (HEMT) 54 2.6 Engineering Application Examples 55 References 62 Problems 63 3 Transmission Lines 71 3.1 Introduction 71 3.2 Transmission Line Analysis 71 3.2.1 Limiting Cases for Transmission Lines 75 3.2.2 Transmission Line Parameters 76 3.2.2.1 Coaxial Line 76 3.2.2.2 Two-wire Transmission Line 80 3.2.2.3 Parallel Plate Transmission Line 80 3.2.3 Terminated Lossless Transmission Lines 81 3.2.4 Special Cases of Terminated Transmission Lines 85 3.2.4.1 Short-circuited Line 85 3.2.4.2 Open-circuited Line 85 3.3 Smith Chart 86 3.3.1 Input Impedance Determination with a Smith Chart 91 3.3.2 Smith Chart as an Admittance Chart 95 3.3.3 ZY Smith Chart and Its Applications 95 3.4 Microstrip Lines 97 3.5 Striplines 104 3.6 Engineering Application Examples 107 References 109 Problems 109 4 Network Parameters 113 4.1 Introduction 113 4.2 Impedance Parameters – Z Parameters 113 4.3 Y Admittance Parameters 116 4.4 ABCD Parameters 117 4.5 h Hybrid Parameters 117 4.6 Network Connections 123 4.7 MATLAB Implementation of Network Parameters 129 4.8 S-Scattering Parameters 141 4.8.1 One-port Network 141 4.8.2 N-port Network 143 4.8.3 Normalized Scattering Parameters 146 4.9 Measurement of S Parameters 154 4.9.1 Measurement of S Parameters for Two-port Network 154 4.9.2 Measurement of S Parameters for a Three-port Network 156 4.10 Chain Scattering Parameters 158 4.11 Engineering Application Examples 160 References 176 Problems 176 5 Impedance Matching 181 5.1 Introduction 181 5.2 Impedance Matching Network with Lumped Elements 181 5.3 Impedance Matching with a Smith Chart – Graphical Method 184 5.4 Impedance Matching Network with Transmission Lines 187 5.4.1 Quarter-wave Transformers 187 5.4.2 Single Stub Tuning 188 5.4.2.1 Shunt Single Stub Tuning 188 5.4.2.2 Series Single Stub Tuning 189 5.4.3 Double Stub Tuning 190 5.5 Impedance Transformation and Matching between Source and Load Impedances 193 5.6 Bandwidth of Matching Networks 195 5.7 Engineering Application Examples 197 References 219 Problems 220 6 Resonator Circuits 223 6.1 Introduction 223 6.2 Parallel and Series Resonant Networks 223 6.2.1 Parallel Resonance 223 6.2.2 Series Resonance 229 6.3 Practical Resonances with Loss, Loading, and Coupling Effects 232 6.3.1 Component Resonances 232 6.3.2 Parallel LC Networks 235 6.3.2.1 Parallel LC Networks with Ideal Components 235 6.3.2.2 Parallel LC Networks with Nonideal Components 236 6.3.2.3 Loading Effects on Parallel LC Networks 237 6.3.2.4 LC Network Transformations 240 6.3.2.5 LC Network with Series Loss 244 6.4 Coupling of Resonators 245 6.5 LC Resonators as Impedance Transformers 249 6.5.1 Inductive Load 249 6.5.2 Capacitive Load 250 6.6 Tapped Resonators as Impedance Transformers 252 6.6.1 Tapped-C Impedance Transformer 252 6.6.2 Tapped-L Impedance Transformer 256 6.7 Engineering Application Examples 256 References 265 Problems 265 7 Couplers, Combiners, and Dividers 271 7.1 Introduction 271 7.2 Directional Couplers 271 7.2.1 Microstrip Directional Couplers 272 7.2.1.1 Two-line Microstrip Directional Couplers 272 7.2.1.2 Three-line Microstrip Directional Couplers 276 7.2.2 Multilayer and Multiline Planar Directional Couplers 279 7.2.3 Transformer Coupled Directional Couplers 281 7.2.3.1 Four-port Directional Coupler Design and Implementation 282 7.2.3.2 Six-port Directional Coupler Design 284 7.3 Multistate Reflectometers 289 7.3.1 Multistate Reflectometer Based on Four-port Network and Variable Attenuator 289 7.4 Combiners and Dividers 292 7.4.1 Analysis of Combiners and Dividers 292 7.4.2 Analysis of Dividers with Different Source Impedance 300 7.4.3 Microstrip Implementation of Combiners/Dividers 313 7.5 Engineering Application Examples 318 References 347 Problems 348 8 Filters 351 8.1 Introduction 351 8.2 Filter Design Procedure 351 8.3 Filter Design by the Insertion Loss Method 360 8.3.1 Low Pass Filters 361 8.3.1.1 Binomial Filter Response 362 8.3.1.2 Chebyshev Filter Response 365 8.3.2 High Pass Filters 376 8.3.3 Bandpass Filters 378 8.3.4 Bandstop Filters 382 8.4 Stepped Impedance Low Pass Filters 383 8.5 Stepped Impedance Resonator Bandpass Filters 386 8.6 Edge/Parallel-coupled, Half-wavelength Resonator Bandpass Filters 388 8.7 End-Coupled, Capacitive Gap, Half-Wavelength Resonator Bandpass Filters 394 8.8 Tunable Tapped Combline Bandpass Filters 400 8.8.1 Network Parameter Representation of Tunable Tapped Filter 402 8.9 Dual Band Bandpass Filters using Composite Transmission Lines 405 8.10 Engineering Application Examples 406 References 422 Problems 422 9 Waveguides 425 9.1 Introduction 425 9.2 Rectangular Waveguides 425 9.2.1 Waveguide Design with Isotropic Media 426 9.2.1.1 TEmn Modes 427 9.2.2 Waveguide Design with Gyrotropic Media 429 9.2.2.1 TEm0 Modes 431 9.2.3 Waveguide Design with Anisotropic Media 432 9.3 Cylindrical Waveguides 442 9.3.1 TE Modes 442 9.3.2 TM Modes 444 9.4 Waveguide Phase Shifter Design 444 9.5 Engineering Application Examples 446 References 454 Problems 454 10 Power Amplifiers 457 10.1 Introduction 457 10.2 Amplifier Parameters 457 10.2.1 Gain 457 10.2.2 Efficiency 459 10.2.3 Power Output Capability 460 10.2.4 Linearity 460 10.2.5 1 dB Compression Point 461 10.2.6 Harmonic Distortion 462 10.2.7 Intermodulation 465 10.3 Small Signal Amplifier Design 470 10.3.1 DC Biasing Circuits 471 10.3.2 BJT Biasing Circuits 472 10.3.2.1 Fixed Bias 473 10.3.2.2 Stable Bias 474 10.3.2.3 Self-bias 475 10.3.2.4 Emitter Bias 476 10.3.2.5 Active Bias Circuit 477 10.3.2.6 Bias Circuit using Linear Regulator 477 10.3.3 FET Biasing Circuits 477 10.3.4 Small Signal Amplifier Design Method 478 10.3.4.1 Definitions Power Gains for Small Signal Amplifiers 478 10.3.4.2 Design Steps for Small Signal Amplifier 482 10.3.4.3 Small Signal Amplifier Stability 483 10.3.4.4 Constant Gain Circles 488 10.3.4.5 Unilateral Figure of Merit 493 10.4 Engineering Application Examples 494 References 508 Problems 509 11 Antennas 513 11.1 Introduction 513 11.2 Antenna Parameters 514 11.3 Wire Antennas 521 11.3.1 Infinitesimal (Hertzian) Dipole (l ≤ λ/50) 521 11.3.2 Short Dipole ( λ/50 ≤ l ≤ λ/10) 524 11.3.3 Half-wave Dipole (l = λ/2) 525 11.4 Microstrip Antennas 531 11.4.1 Type of Patch Antennas 533 11.4.2 Feeding Methods 533 11.4.2.1 Microstrip Line Feed 533 11.4.2.2 Proximity Coupling 536 11.4.3 Microstrip Antenna Analysis – Transmission Line Method 536 11.4.4 Impedance Matching 537 11.5 Engineering Application Examples 539 References 552 Problems 552 12 RF Wireless Communication Basics for Emerging Technologies 555 12.1 Introduction 555 12.2 Wireless Technology Basics 555 12.3 Standard Protocol vs Proprietary Protocol 556 12.3.1 Standard Protocols 556 12.3.2 Proprietary Protocols 556 12.3.2.1 Physical Layer Only Approach 557 12.4 Overview of Protocols 557 12.4.1 ZigBee 557 12.4.2 LowPAN 558 12.4.3 Wi-Fi 558 12.4.4 Bluetooth 560 12.5 RFIDs 560 12.5.1 Active RFID Tags 562 12.5.2 Passive RFID Tags 562 12.5.3 RFID Frequencies 562 12.5.3.1 Low Frequency ~124 kHz and High Frequency ~13.56 MHz 562 12.5.3.2 Ultrahigh Frequency (UHF) Tags ~423 MHz–2.45 GHz 563 12.6 RF Technology for Implantable Medical Devices 563 12.6.1 Challenges with IMDs 564 12.6.1.1 Biocompatibility 564 12.6.1.2 Frequency 564 12.6.1.3 Dimension Constraints 564 12.7 Engineering Application Examples 565 References 576 13 Energy Harvesting and HVAC Systems with RF Signals 577 13.1 Introduction 577 13.2 RF Energy Harvesting 577 13.3 RF Energy Harvesting System Design for Dual Band Operation 578 13.3.1 Matching Network for Energy Harvester 580 13.3.2 RF–DC Conversion for Energy Harvester 582 13.3.3 Clamper and Peak Detector Circuits 582 13.3.4 Cascaded Rectifier 584 13.3.5 Villard Voltage Multiplier 584 13.3.6 RF–DC Rectifier Stages 584 13.4 Diode Threshold Vth Cancellation 585 13.4.1 Internal Vth Cancellation 585 13.4.2 External Vth Cancellation 586 13.4.3 Self-Vth Cancellation 586 13.5 HVAC Systems 587 13.6 Engineering Application Examples 588 References 609 Index 611

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Book SynopsisAn in-depth review of hybrid control techniques for smart prosthetic hand technology by two of the world's pioneering experts in the field Long considered the stuff of science fiction, a prosthetic hand capable of fully replicating all of that appendage's various functions is closer to becoming reality than ever before. This book provides a comprehensive report on exciting recent developments in hybrid control techniquesone of the most crucial hurdles to be overcome in creating smart prosthetic hands. Coauthored by two of the world's foremost pioneering experts in the field, Fusion of Hard and Soft Control Strategies for Robotic Hand treats robotic hands for multiple applications. Itbegins withan overview of advances in main control techniques that have been made over the past decade before addressing the military context foraffordable robotic hand technology with tactile and/or proprioceptive feedbackfor hand amputees. Kinematics, homogeneous transformations, inverse and differentiTable of ContentsList of Figures xi List of Tables xvii 1 Introduction 1 1.1 Relevance to Military 2 1.2 Control Strategies 3 1.2.1 Prosthetic/Robotic Hands 3 1.2.2 Chronological Overview 5 1.2.3 Overview of Main Control Techniques Since 2007 15 1.2.4 Revolutionary Prosthesis 18 1.3 Fusion of Intelligent Control Strategies 19 1.3.1 Fusion of Hard and Soft Computing/Control Strategies 19 1.4 Overview of Our Research 22 1.5 Developments in Neuroprosthetics 23 1.6 Chapter Summary 24 2 Kinematics and Trajectory Planning 47 2.1 Human Hand Anatomy 48 2.2 Forward Kinematics 49 2.2.1 Homogeneous Transformations 50 2.2.2 Serial -Link Revolute-Joint Planar Manipulator 54 2.2.3 Two-Link Thumb 58 2.2.4 Three-Link Index Finger 60 2.2.5 Three-Dimensional Five-Fingered Robotic Hand 62 2.3 Inverse Kinematics 66 2.3.1 Two-Link Thumb 66 2.3.2 Three-Link Fingers 67 2.3.3 Fingertip Workspace 68 2.3.3.1 Two-Link Thumb and Three-Link Index Finger 69 2.3.3.2 Five-Fingered Robotic Hand 70 2.4 Differential Kinematics 70 2.4.1 Serial -Link Revolute-Joint Planar Manipulator 71 2.4.1.1 Some Properties of RotationMatrices 72 2.4.1.2 Rigid Body Kinematics 74 2.4.2 Two-Link Thumb 78 2.4.3 Three-Link Index Finger 79 2.5 Trajectory Planning 80 2.5.1 Trajectory Planning Using Cubic Polynomial 81 2.5.2 Trajectory Planning Using Cubic Bezier Curve 82 2.5.3 Simulation Results of Trajectory Paths 84 3 Dynamic Models 93 3.1 Actuators 93 3.1.1 Electric DC Motor 93 3.1.2 Mechanical Gear Transmission 94 3.2 Dynamics 96 3.3 Two-Link Thumb 96 3.4 Three-Link Index Finger 99 4 Soft Computing/Control Strategies 105 4.1 Fuzzy Logic 105 4.2 Neural Network 108 4.3 Adaptive Neuro-Fuzzy Inference System 108 4.4 Tabu Search 113 4.4.1 Tabu Concepts 113 4.4.2 Enhanced Continuous Tabu Search 114 4.4.2.1 Initialization of Parameters 114 4.4.2.2 Diversification 114 4.4.2.3 Selecting the Most Promising Area 115 4.4.2.4 Intensi cation 116 4.5 Genetic Algorithm 118 4.5.1 Basic GA Procedures 118 4.6 Particle Swarm Optimization 121 4.6.1 Basic PSO Procedures and Formulations 121 4.6.2 Five Different PSO Techniques 125 4.6.3 Uniform Distribution and Normal Distribution 128 4.7 Adaptive Particle Swarm Optimization 130 4.7.1 APSO Procedures and Formulations 130 4.7.2 Changed/Unchanged Velocity Direction 134 4.8 Condensed Hybrid Optimization 136 4.9 Simulation Results and Discussion 137 4.9.1 PSO Dynamics Investigation 137 4.9.1.1 Benchmark Problems 137 4.9.1.2 Selection of Parameters 138 4.9.1.3 Simulations 139 4.9.2 APSO to Multiple Dimensional Problems 145 4.9.3 PSO in Other Biomedical Applications 149 4.9.3.1 Leukocyte Adhesion Molecules Modeling 149 4.9.4 CHO to Multiple Dimensional Problems 151 5 Fusion of Hard and Soft Control Strategies I 161 5.1 Feedback Linearization 161 5.1.1 State Variable Representation 162 5.2 PD/PI/PID Controllers 163 5.2.1 PD Controller 164 5.2.2 PI Controller 165 5.2.3 PID Controller 165 5.3 Optimal Controller 167 5.3.1 Optimal Regulation 167 5.3.2 Linear Quadratic Optimal Control with Tracking System 167 5.3.3 A Modified Optimal Control with Tracking System 168 5.4 Adaptive Controller 170 5.5 Simulation Results and Discussion 172 5.5.1 Two-Link Thumb 172 5.5.2 Three-Link Index Finger 175 5.5.3 Three-Dimensional Five-Fingered Robotic Hand 177 5.5.3.1 PID Control 177 5.5.3.2 Optimal Control 178 5.A Appendix: Regression Matrix 198 6 Fusion of Hard and Soft Control Strategies II 203 6.1 Fuzzy-Logic-Based PD Fusion Control Strategy 203 6.1.1 Simulation Results and Discussion 207 6.2 Genetic-Algorithm-Based PID Fusion Control Strategy 212 6.2.1 Simulation Results and Discussion 213 7 Conclusions and Future Work 223 7.1 Conclusions 223 7.2 Future Directions 225 Index 229 Epilogue 231

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Book Synopsis5G BACKHAUL AND FRONTHAUL In-depth coverage of all technologies required for deployment and further evolution of 5G mobile network backhaul and fronthaul In this book, a team of communications technology experts deliver an up-to-date and technical discussion of 5G backhaul and fronthaul, preparing readers for the deployment of 5G technologies, covering the technologies essentials, and offering views of further 5G backhaul and fronthaul evolution. 5G Backhaul and Fronthaul serves both advanced-level experts with senior roles in organizations who are already proficient in these technologies, and general interest readers seeking a primer on what these technologies can provide. Readers will also find: Thorough introductions to 5G backhaul and fronthaul, as well as selected industry forums and activities Analysis of high-level requirements for 5G backhaul and fronthaul and 5G network architecture In-depth explorations of wireless backhaul and fronthaul access technologies, including fiber Table of ContentsAcknowledgements xi About the Editors xiii List of Contributors xv 1 Introduction 1 Esa Metsälä and Juha Salmelin 1.1 Introducing 5G in Transport 1 1.2 Targets of the Book 3 1.3 Backhaul and Fronthaul Scope within the 5G System 3 1.4 Arranging Connectivity within the 5G System 4 1.5 Standardization Environment 5 1.5.1 3GPP and other organizations 5 References 8 2 5G System Design Targets and Main Technologies 11 Harri Holma and Antti Toskala 11 2.1 5G System Target 11 2.2 5G Technology Components 12 2.3 Network Architecture 14 2.4 Spectrum and Coverage 21 2.5 Beamforming 22 2.6 Capacity 24 2.6.1 Capacity per Cell 24 2.6.2 Capacity per Square Kilometre 24 2.7 Latency and Architecture 26 2.8 Protocol Optimization 28 2.8.1 Connectionless RRC 28 2.8.2 Contention-Based Access 28 2.8.3 Pipelining 29 2.9 Network Slicing and QoS 30 2.10 Integrated Access and Backhaul 32 2.11 Ultra Reliable and Low Latency 33 2.12 Open RAN 34 2.13 3GPP Evolution in Release 16/17 36 2.14 5G-Advanced 38 References 39 3 5G RAN Architecture and Connectivity – A Techno-economic Review 41 Andy Sutton 3.1 Introduction 41 3.2 Multi-RAT Backhaul 41 3.3 C-RAN and LTE Fronthaul 43 3.4 5G RAN Architecture 44 3.5 5G D-RAN Backhaul Architecture and Dimensioning 46 3.6 Integrating 5G within a Multi-RAT Backhaul Network 48 3.7 Use Case – BT/EE 5G Network in the UK 51 3.8 5G C-RAN – F1 Interface and Midhaul 55 3.9 5G C-RAN – CPRI, eCPRI and Fronthaul 56 3.10 Connectivity Solutions for Fronthaul 59 3.11 Small Cells in FR1 and FR 2 62 3.12 Summary 62 References 63 4 Key 5G Transport Requirements 65 Kenneth Y. Ho and Esa Metsälä 4.1 Transport Capacity 65 4.1.1 5G Radio Impacts to Transport 65 4.1.2 Backhaul and Midhaul Dimensioning Strategies 67 4.1.3 Protocol Overheads 68 4.1.4 Backhaul and Midhaul Capacity 69 4.1.5 Fronthaul Capacity 70 4.1.6 Ethernet Link Speeds 71 4.2 Transport Delay 73 4.2.1 Contributors to Delay in 5G System 73 4.2.2 Allowable Transport Delay 73 4.2.3 User Plane and Control Plane Latency for the Logical Interfaces 75 4.2.4 Fronthaul (Low-Layer Split Point) 76 4.2.5 Low-Latency Use Cases 77 4.3 Transport Bit Errors and Packet Loss 78 4.3.1 Radio-Layer Performance and Retransmissions 78 4.3.2 Transport Bit Errors and Packet Loss 79 4.4 Availability and Reliability 80 4.4.1 Definitions 80 4.4.2 Availability Targets 81 4.4.3 Availability in Backhaul Networks 82 4.4.4 Recovery Times in Backhaul and Fronthaul 84 4.4.5 Transport Reliability 84 4.4.6 Air Interface Retransmissions and Transport Reliability 87 4.4.7 Packet Duplication in 5G and Transport 88 4.4.8 Transport Analysis Summary for Availability and Reliability 90 4.5 Security 91 4.5.1 Summary of 5G Cryptographic Protection 91 4.5.2 Network Domain Protection 92 4.5.3 Security in Fronthaul 92 4.6 Analysis for 5G Synchronization Requirement 92 4.6.1 Frequency Error 93 4.6.2 Time Alignment Error (Due to TDD Timing) 93 4.6.3 Time Alignment Error (Due to MIMO) 100 4.6.4 Time Alignment Error (Due to Carrier Aggregation) 101 4.6.5 Time Alignment Accuracy (Due to Other Advanced Features) 102 References 102 5 Further 5G Network Topics 105 Esa Malkamäki, Mika Aalto, Juha Salmelin and Esa Metsälä 5.1 Transport Network Slicing 105 5.1.1 5G System-Level Operation 105 5.1.2 Transport Layers 105 5.2 Integrated Access and Backhaul 108 5.2.1 Introduction 108 5.2.2 IAB Architecture 109 5.2.3 Deployment Scenarios and Use Cases 110 5.2.4 IAB Protocol Stacks 111 5.2.5 IAB User Plane 113 5.2.6 IAB Signalling Procedures 114 5.2.7 Backhaul Adaptation Protocol 116 5.2.8 BH Link Failure Handling 117 5.2.9 IAB in 3GPP Release 17 and Beyond 118 5.3 Ntn 118 5.3.1 NTN in 3GPP 118 5.3.2 Different Access Types 119 5.3.3 Protocol Stacks 121 5.3.4 Transparent Architecture 123 5.3.5 Feeder Link Switchover 124 5.4 URLLC Services and Transport 125 5.4.1 Background 125 5.4.2 Reliability 127 5.4.3 Latency 128 5.5 Industry Solutions and Private 5G 129 5.5.1 Introduction to Private 5G Networking 129 5.5.2 3GPP Features Supporting Private 5G Use Cases 130 5.5.3 URLLC and TSC in Private 5G 133 5.6 Smart Cities 133 5.6.1 Needs of Cities 134 5.6.2 Possible Solutions 135 5.6.3 New Business Models 137 5.6.4 Implications for BH/FH 138 References 139 6 Fibre Backhaul and Fronthaul 141 Pascal Dom, Lieven Levrau, Derrick Remedios and Juha Salmelin 6.1 5G Backhaul/Fronthaul Transport Network Requirements 141 6.1.1 Capacity Challenge 141 6.1.2 Latency Challenge 143 6.1.3 Synchronization Challenge 144 6.1.4 Availability Challenge 144 6.1.5 Software-Controlled Networking for Slicing Challenge 145 6.1.6 Programmability and OAM Challenges 145 6.2 Transport Network Fibre Infrastructure 146 6.2.1 Availability of Fibre Connectivity 146 6.2.2 Dedicated vs Shared Fibre Infrastructure 147 6.2.3 Dedicated Infrastructure 149 6.2.4 Shared Infrastructure 149 6.3 New Builds vs Legacy Infrastructure 150 6.4 Optical Transport Characteristics 151 6.4.1 Optical Fibre Attenuation 151 6.4.2 Optical Fibre Dispersion 152 6.5 TSN Transport Network for the Low-Layer Fronthaul 153 6.6 TDM-PONs 154 6.6.1 TDM-PONs as Switched Transport Network for Backhaul and Midhaul 154 6.6.2 TDM-PONs as Switched Transport Network for Fronthaul 156 6.7 Wavelength Division Multiplexing Connectivity 156 6.7.1 Passive WDM Architecture 156 6.7.2 Active–Active WDM Architecture 158 6.7.3 Semi-Active WDM Architecture 160 6.8 Total Cost of Ownership for Fronthaul Transport Networking 161 References 163 7 Wireless Backhaul and Fronthaul 165 Paolo Di Prisco, Antti Pietiläinen and Juha Salmelin 7.1 Baseline 165 7.2 Outlook 166 7.3 Use Cases Densification and Network Upgrade 169 7.4 Architecture Evolution – Fronthaul/Midhaul/Backhaul 172 7.5 Market Trends and Drivers 172 7.5.1 Data Capacity Increase 173 7.5.2 Full Outdoor 174 7.5.3 New Services and Slicing 174 7.5.4 End-to-End Automation 175 7.6 Tools for Capacity Boost 176 7.6.1 mmW Technology (Below 100 GHz) 176 7.6.2 Carrier Aggregation 177 7.6.3 New Spectrum Above 100 GHz 181 7.7 Radio Links Conclusions 183 7.8 Free-Space Optics 183 7.8.1 Introduction 183 7.8.2 Power Budget Calculations 184 7.8.3 Geometric Loss 184 7.8.4 Atmospheric Attenuation 185 7.8.5 Estimating Practical Link Spans 186 7.8.6 Prospects of FSO 188 References 189 8 Networking Services and Technologies 191 Akash Dutta and Esa Metsälä 8.1 Cloud Technologies 191 8.1.1 Data Centre and Cloud Infrastructure 191 8.1.2 Data Centre Networking 194 8.1.3 Network Function Virtualization 196 8.1.4 Virtual Machines and Containers 198 8.1.5 Accelerators for RAN Functions 202 8.1.6 O-RAN View on Virtualization and Cloud Infrastructure 204 8.2 Arranging Connectivity 206 8.2.1 IP and MPLS for Connectivity Services 206 8.2.2 Traffic Engineering with MPLS-TE 208 8.2.3 E-vpn 208 8.2.4 Segment Routing 210 8.2.5 IP and Optical 211 8.2.6 IPv4 and IPv 6 212 8.2.7 Routing Protocols 212 8.2.8 Loop-Free Alternates 214 8.2.9 Carrier Ethernet Services 215 8.2.10 Ethernet Link Aggregation 216 8.3 Securing the Network 217 8.3.1 IPsec and IKEv 2 217 8.3.2 Link-Layer Security (MACSEC) 219 8.3.3 Dtls 220 8.4 Time-Sensitive Networking and Deterministic Networks 220 8.4.1 Motivation for TSN 220 8.4.2 IEEE 802.1CM – TSN for Fronthaul 221 8.4.3 Frame Pre-emption 223 8.4.4 Frame Replication and Elimination 223 8.4.5 Management 225 8.4.6 Deterministic Networks 226 8.5 Programmable Network and Operability 227 8.5.1 Software-Defined Networking Initially 227 8.5.2 Benefits with Central Controller 228 8.5.3 Netconf/YANG 229 References 230 9 Network Deployment 233 Mika Aalto, Akash Dutta, Kenneth Y. Ho, Raija Lilius and Esa Metsälä 9.1 NSA and SA Deployments 233 9.1.1 Shared Transport 233 9.1.2 NSA 3x Mode 235 9.1.3 SA Mode 237 9.2 Cloud RAN Deployments 237 9.2.1 Motivation for Cloud RAN 237 9.2.2 Pooling and Scalability in CU 240 9.2.3 High Availability in CU 242 9.2.4 Evolving to Real-Time Cloud – vDU 244 9.2.5 Enterprise/Private Wireless 250 9.3 Fronthaul Deployment 251 9.3.1 Site Solutions and Fronthaul 251 9.3.2 Carrying CPRI over Packet Fronthaul 252 9.3.3 Statistical Multiplexing Gain 253 9.3.4 Merged Backhaul and Fronthaul 255 9.4 Indoor Deployment 257 9.5 Deploying URLLC and Enterprise Networks 262 9.5.1 Private 5G Examples 262 9.5.2 Private 5G RAN Architecture Evolution 264 9.5.3 IP Backhaul and Midhaul Options for Private 5G 266 9.5.4 Fronthaul for Private 5G 266 9.5.5 Other Transport Aspects in Private 5G Networks 267 9.6 Delivering Synchronization 268 9.6.1 Network Timing Synchronization Using PTP and SyncE 269 9.6.2 SyncE 269 9.6.3 IEEE 1588 (aka PTP) 270 9.6.4 ITU-T Profiles for Telecom Industry Using SyncE and PTP 270 9.6.5 Example of Putting All Standards Together in Planning 271 9.6.6 Resilience Considerations in Network Timing Synchronization 275 9.6.7 QoS Considerations in Network Timing Synchronization 276 9.6.8 Special Considerations in Cloud RAN Deployment 276 9.6.9 Satellite-Based Synchronization 277 9.6.10 Conclusion for Synchronization 278 References 278 10 Conclusions and Path for the Future 279 Esa Metsälä and Juha Salmelin 10.1 5G Path for the Future 279 10.2 Summary of Content 280 10.3 Evolutionary Views for Backhaul and Fronthaul 280 Index 283

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Book SynopsisPractical Guide Provides Students and Industry Professionals with Latest Information on 5G Mobile Networks Continuing the tradition established in his previous publications, Jyrki Penttinen offers 5G Explained as a thorough yet concise introduction to recent advancements and growing trends in mobile telecommunications. In this case, Penttinen focuses on the development and employment of 5G mobile networks and, more specifically, the challenges inherent in adjusting to new global standardization requirements and in maintaining a high level of security even as mobile technology expands to new horizons. The text discusses, for example, the Internet of Things (IoT) and how to keep networks reliable and secure when they are constantly accessed by many different devices with varying levels of user involvement and competence. 5G Explained is primarily designed for specialists who need rapid acclimation to the possibilities and concerns presented by 5G adoTable of ContentsAuthor Biography xv Preface xvii Acknowledgments xix Abbreviation List xxi 1 Introduction 1 1.1 Overview 1 1.2 What Is 5G? 2 1.3 Background 3 1.4 Research 4 1.5 Challenges for Electronics 4 1.6 Expected 5G in Practice 5 1.7 5G and Security 7 1.8 Motivations 7 1.9 5G Standardization and Regulation 7 1.10 Global Standardization in 5G Era 11 1.11 Introduction to the Book 17 References 18 2 Requirements 21 2.1 Overview 21 2.2 Background 22 2.3 5G Requirements Based on ITU 23 2.4 The Technical Specifications of 3GPP 29 2.5 NGMN 38 2.6 Mobile Network Operators 43 2.7 Mobile Device Manufacturers 43 References 44 3 Positioning of 5G 47 3.1 Overview 47 3.2 Mobile Generations 47 3.3 The Role of 3GPP in LPWA and IoT 56 3.4 The Role of 5G in Automotive (V2X) 63 3.5 The Role of 5G in the Cyber-World 63 References 69 4 Architecture 71 4.1 Overview 71 4.2 Architecture 72 4.3 Renewed Functionality of the 5G System 92 4.4 Supporting Solutions for 5G 97 4.5 Control and User Plane Separation of EPC Nodes (CUPS) 100 References 102 5 Radio Network 105 5.1 Overview 105 5.2 5G Performance 106 5.3 5G Spectrum 107 5.4 5G Radio Access Technologies 112 5.5 Uplink OFDM of 5G: CP-OFDM and DFT-s-OFDM 124 5.6 Downlink 124 5.7 New Radio (NR) Interface of 3GPP 126 5.8 User Devices 133 5.9 Other Aspects 134 5.10 CBRS 134 References 137 6 Core Network 139 6.1 Overview 139 6.2 Preparing the Core for 5G 141 6.3 5G Core Network Elements 154 6.4 5G Functionalities Implemented in 5G Core 165 6.5 Transport Network 170 6.6 Protocols and Interfaces 173 References 185 7 Services and Applications 187 7.1 Overview 187 7.2 5G Services 188 7.3 Network Function-Related Cases 195 7.4 Vehicle Communications 197 7.5 Machine Learning and Artificial Intelligence 202 References 202 8 Security 205 8.1 Overview 205 8.2 5G Security Threats and Challenges 208 8.3 Development 213 8.4 Security Implications in 5G Environments and Use Cases 214 8.5 5G Security Layers 219 8.6 Device Security 220 8.7 Security between Network Entities 226 8.8 Security Opportunities for Stakeholders 227 8.9 5G Security Architecture for 3GPP Networks 229 8.10 UICC Evolution 239 8.11 5G Security Development 243 8.12 UICC Variants 243 References 252 9 5G Network Planning and Optimization 255 9.1 Overview 255 9.2 5G Core and Transmission Network Dimensioning 255 9.3 5G Radio Network Planning 259 References 268 10 Deployment 271 10.1 Overview 271 10.2 Trials and Early Adopters Prior to 2020 271 10.3 5G Frequency Bands 272 10.4 Core and Radio Network Deployment Scenarios 273 10.5 Standalone and Non-Standalone Deployment Scenarios 276 10.6 5G Network Interfaces and Elements 281 10.7 Core Deployment 282 10.8 CoMP 283 10.9 Measurements 284 References 290 Index 293

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Book SynopsisNew and updated English translation of the highly successful book on digital media This book introduces readers to the vast and rich world of digital media. It provides a strong starting point for understanding digital media's social and political significance to our culture and the culture of othersdrawing on an emergent and increasingly rich set of empirical and theoretical studies on the role and development of digital media in contemporary societies. Touching on the core points behind the discipline, the book addresses a wide range of topics, including media economics, online cooperation, open source, social media, software production, globalization, brands, marketing, the cultural industry, labor, and consumption. Presented in six sectionsMedia and Digital Technologies; The Information Society; Cultures and Identities; Digital Collaboration; Public Sphere and Power; Digital Economiesthe book offers in-depth chapter coverage of new and old media; network infrastructure; networkeTable of ContentsPreface vii Part I Frameworks 1 1 Media and Digital Technologies 3 1.1 The Digital Environment 3 1.2 New and Old Media 6 1.3 Digital Media 8 1.4 Infrastructures and Platforms 13 1.5 Technology and Society 15 2 The Information Society 21 2.1 A New Society? 21 2.2 The Networked Economy and Globalization 23 2.3 Theories of the Information Society 27 2.4 The History of Information Technologies 31 2.5 The Evolution of Networks 38 2.6 The Future of the Information Society 42 Part II Transformations 45 3 Cultures and Identities 47 3.1 Digital Sociality 47 3.2 Social Media 51 3.3 Media and Identity 54 3.4 Communities or Publics? 59 3.5 Reputation and Influence 63 3.6 Critiques of Digital Sociality 66 4 From Collaboration to Value 71 4.1 Collaborative Media 71 4.2 The Dilemma of Participation 75 4.3 From Free Software to Peer‐to‐Peer 77 4.4 Open Innovation 83 4.5 The Economic Value of Cooperation 88 5 The Public Sphere and Power 93 5.1 From Audiences to Active Publics 93 5.2 Journalism and the Public Sphere 95 5.3 Politics and Democracy 102 5.4 Social Movements 106 5.5 Surveillance and Control 110 5.6 Information and Civic Culture 114 6 Work and Economy 117 6.1 The Rise of Digital Capitalism 117 6.2 Economic Models and Actors 119 6.3 Digital Labor and Precarity 125 6.4 Immaterial Production: Brands and Finance 135 6.5 Global Inequalities and Development 140 Conclusion 145 Glossary 149 References 155 Index 171

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Book SynopsisGets you quickly up to speed with the theoretical and practical aspects of free space optical systems engineering design and analysis One of today''s fastest growing system design and analysis disciplines is free space optical systems engineering for communications and remote sensing applications. It is concerned with creating a light signal with certain characteristics, how this signal is affected and changed by the medium it traverses, how these effects can be mitigated both pre- and post-detection, and if after detection, it can be differentiated from noise under a certain standard, e.g., receiver operating characteristic. Free space optical systems engineering is a complex process to design against and analyze. While there are several good introductory texts devoted to key aspects of opticssuch as lens design, lasers, detectors, fiber and free space, optical communications, and remote sensinguntil now, there were none offering comprehensive coverage of the basics nTable of ContentsPreface xii About the Companion Website xvi 1 Mathematical Preliminaries 1 1.1 Introduction 1 1.2 Linear Algebra 1 1.2.1 Matrices and Vectors 2 1.2.2 Linear Operations 2 1.2.3 Traces, Determinants, and Inverses 3 1.2.4 Inner Products, Norms, and Orthogonality 7 1.2.5 Eigenvalues, Eigenvectors, and Rank 8 1.2.6 Quadratic Forms and Positive Definite Matrices 8 1.2.7 Gradients, Jacobians, and Hessians 8 1.3 Fourier Series 9 1.3.1 Real Fourier Series 9 1.3.2 Complex Fourier Series 10 1.3.3 Effects of Finite Fourier Series Use 11 1.3.4 Some Useful Properties of Fourier Series 14 1.4 Fourier Transforms 15 1.4.1 Some General Properties 15 1.5 Dirac Delta Function 20 1.6 Probability Theory 21 1.6.1 Axioms of Probability 21 1.6.2 Conditional Probabilities 23 1.6.3 Probability and Cumulative Density Functions 25 1.6.4 Probability Mass Function 27 1.6.5 Expectation and Moments of a Scalar Random Variable 28 1.6.6 Joint PDF and CDF of Two Random Variables 29 1.6.7 Independent Random Variables 29 1.6.8 Vector-Valued Random Variables 30 1.6.9 Gaussian Random Variables 31 1.6.10 Quadratic and Quartic Forms 33 1.6.11 Chi-Squared Distributed Random Variable 34 1.6.12 Binomial Distribution 35 1.6.13 Poisson Distribution 37 1.6.14 Random Processes 38 1.7 Decibels 40 1.8 Problems 42 References 48 2 Fourier Optics Basics 51 2.1 Introduction 51 2.2 The Maxwell Equations 52 2.3 The Rayleigh–Sommerfeld–Debye Theory of Diffraction 55 2.4 The Huygens–Fresnel–Kirchhoff Theory of Diffraction 59 2.5 Fraunhofer Diffraction 68 2.6 Bringing Fraunhofer Diffraction into the Near Field 76 2.7 Imperfect Imaging 82 2.8 The Rayleigh Resolution Criterion 84 2.9 The Sampling Theorem 85 2.10 Problems 89 References 93 3 Geometrical Optics 95 3.1 Introduction 95 3.2 The Foundations of Geometrical Optics – Eikonal Equation and Fermat Principle 96 3.3 Refraction and Reflection of Light Rays 98 3.4 Geometrical Optics Nomenclature 101 3.5 Imaging System Design Basics 103 3.6 Optical Invariant 109 3.7 Another View of Lens Theory 111 3.8 Apertures and Field Stops 113 3.8.1 Aperture Stop 113 3.8.2 Entrance and Exit Pupils 114 3.8.3 Field Stop and Chief and Marginal Rays 115 3.8.4 Entrance and Exit Windows 117 3.8.5 Baffles 119 3.9 Problems 119 References 121 4 Radiometry 123 4.1 Introduction 123 4.2 Basic Geometrical Definitions 124 4.3 Radiometric Parameters 127 4.3.1 Radiant Flux (Radiant Power) 129 4.3.2 Radiant Intensity 130 4.3.3 Radiance 130 4.3.4 Étendue 132 4.3.5 Radiant Flux Density (Irradiance and Radiant Exitance) 135 4.3.6 Bidirectional Reflectance Distribution Function 135 4.3.7 Directional Hemispheric Reflectance 136 4.3.8 Specular Surfaces 136 4.4 Lambertian Surfaces and Albedo 137 4.5 Spectral Radiant Emittance and Power 138 4.6 Irradiance from a Lambertian Source 139 4.7 The Radiometry of Images 143 4.8 Blackbody Radiation Sources 145 4.9 Problems 151 References 151 5 Characterizing Optical Imaging Performance 153 5.1 Introduction 153 5.2 Linearity and Space Variance of the Optical System or Optical Channel 154 5.3 Spatial Filter Theory of Image Formation 156 5.4 Linear Filter Theory of Incoherent Image Formation 160 5.5 The Modulation Transfer Function 162 5.6 The Duffieux Formula 167 5.7 Obscured Aperture OTF 174 5.7.1 Aberrations 179 5.8 High-Order Aberration Effects Characterization 184 5.9 The Strehl Ratio 191 5.10 Multiple Systems Transfer Function 193 5.11 Linear Systems Summary 195 References 198 6 Partial Coherence Theory 201 6.1 Introduction 201 6.2 Radiation Fluctuation 202 6.3 Interference and Temporal Coherence 205 6.4 Interference and Spatial Coherence 214 6.5 Coherent Light Propagating Through a Simple Lens System 219 6.6 Partially Coherent Imaging Through any Optical System 231 6.7 Van Cittert–Zernike Theorem 233 6.8 Problems 235 References 237 7 Optical Channel Effects 239 7.1 Introduction 239 7.2 Essential Concepts in Radiative Transfer 239 7.3 The Radiative Transfer Equation 245 7.4 Mutual Coherence Function for an Aerosol Atmosphere 251 7.5 Mutual Coherence Function for a Molecular Atmosphere 255 7.6 Mutual Coherence Function for an Inhomogeneous Turbulent Atmosphere 256 7.7 Laser Beam Propagation in the Total Atmosphere 262 7.8 Key Parameters for Analyzing Light Propagation Through Gradient Turbulence 272 7.9 Two Refractive Index Structure Parameter Models for the Earth’s Atmosphere 278 7.10 Engineering Equations for Light Propagation in the Ocean and Clouds 282 7.11 Problems 294 References 295 8 Optical Receivers 299 8.1 Introduction 299 8.2 Optical Detectors 300 8.2.1 Performance Criteria 300 8.2.2 Thermal Detectors 302 8.2.3 Photoemissive Detectors 302 8.2.4 Semiconductor Photodetectors 305 8.2.5 Photodiode Array and Charge-Coupled Devices 325 8.3 Noise Mechanisms in Optical Receivers 325 8.3.1 Shot Noise 326 8.3.2 Erbium-Doped Fiber Amplifier (EDFA) Noise 330 8.3.3 Relative Intensity Noise 331 8.3.4 More Conventional Noise Sources 333 8.4 Performance Measures 335 8.4.1 Signal-to-Noise Ratio 336 8.4.2 The Optical Signal-to-Noise Ratio 338 8.4.3 The Many Faces of the Signal-to-Noise Ratio 345 8.4.4 Noise Equivalent Power and Minimum Detectable Power 346 8.4.5 Receiver Sensitivity 347 8.5 Problems 350 References 353 9 Signal Detection and Estimation Theory 355 9.1 Introduction 355 9.2 Classical Statistical Detection Theory 356 9.2.1 The Bayes Criterion 358 9.2.2 The Minimax Criterion 360 9.2.3 The Neyman–Pearson Criterion 361 9.3 Testing of Simple Hypotheses Using Multiple Measurements 365 9.4 Constant False Alarm Rate (CFAR) Detection 374 9.5 Optical Communications 375 9.5.1 Receiver Sensitivity for System Noise-Limited Communications 375 9.5.2 Receiver Sensitivity for Quantum-Limited Communications 381 9.6 Laser Radar (LADAR) and LIDAR 389 9.6.1 Background 389 9.6.2 Coherent Laser Radar 392 9.6.3 Continuous Direct Detection Intensity Statistics 398 9.6.4 Photon-Counting Direct Detection Intensity Statistics 401 9.6.5 LIDAR 404 9.7 Resolved Target Detection in Correlated Background Clutter and Common System Noise 408 9.8 Zero Contrast Target Detection in Background Clutter 415 9.9 Multispectral Signal-Plus-Noise/Noise-Only Target Detection in Clutter 416 9.10 Resolved Target Detection in Correlated Dual-Band Multispectral Image Sets 427 9.11 Image Whitener 434 9.11.1 Orthogonal Sets 434 9.11.2 Gram–Schmidt Orthogonalization Theory 435 9.11.3 Prewhitening Filter Using the Gram–Schmidt Process 436 9.12 Problems 437 References 440 10 Laser Sources 443 10.1 Introduction 443 10.2 Spontaneous and Stimulated Emission Processes 444 10.2.1 The Two-Level System 444 10.2.2 The Three-Level System 451 10.2.3 The Four-Level System 453 10.3 Laser Pumping 454 10.3.1 Laser Pumping without Amplifier Radiation 454 10.3.2 Laser Pumping with Amplifier Radiation 455 10.4 Laser Gain and Phase-Shift Coefficients 456 10.5 Laser Cavity Gains and Losses 463 10.6 Optical Resonators 466 10.6.1 Planar Mirror Resonators – Longitudinal Modes 466 10.6.2 Planar Mirror Resonators – Transverse Modes 471 10.7 The ABCD Matrix and Resonator Stability 474 10.8 Stability of a Two-Mirror Resonator 477 10.9 Problems 479 References 482 Appendix A STATIONARY PHASE AND SADDLE POINT METHODS 485 A.1 Introduction 485 A.2 The Method of Stationary Phase 485 A.3 Saddle Point Method 487 Appendix B EYE DIAGRAM AND ITS INTERPRETATION 489 B.1 Introduction 489 B.2 Eye Diagram Overview 489 Appendix C VECTOR-SPACE IMAGE REPRESENTATION 491 C.1 Introduction 491 C.2 Basic Formalism 491 Reference 493 Appendix D PARAXIAL RAY TRACING – ABCD MATRIX 495 D.1 Introduction 495 D.2 Basic Formalism 495 D.2.1 Propagation in a Homogeneous Medium 497 D.2.2 Propagation Against a Curved Interface 498 D.2.3 Propagation into a Refractive Index Interface 499 References 502 Index 503

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Book SynopsisLearn the technology behind hearing aids, Siri, and Echo Audio source separation and speech enhancement aim to extract one or more source signals of interest from an audio recording involving several sound sources.Table of ContentsList of Authors xvii Preface xxi Acknowledgment xxiii Notations xxv Acronyms xxix About the Companion Website xxxi Part I Prerequisites 1 1 Introduction 3Emmanuel Vincent, Sharon Gannot, and Tuomas Virtanen 1.1 Why are Source Separation and Speech Enhancement Needed? 3 1.2 What are the Goals of Source Separation and Speech Enhancement? 4 1.3 How can Source Separation and Speech Enhancement be Addressed? 9 1.4 Outline 11 Bibliography 12 2 Time-Frequency Processing: Spectral Properties 15Tuomas Virtanen, Emmanuel Vincent, and Sharon Gannot 2.1 Time-Frequency Analysis and Synthesis 15 2.2 Source Properties in the Time-Frequency Domain 23 2.3 Filtering in the Time-Frequency Domain 25 2.4 Summary 28 Bibliography 28 3 Acoustics: Spatial Properties 31Emmanuel Vincent, Sharon Gannot, and Tuomas Virtanen 3.1 Formalization of the Mixing Process 31 3.2 Microphone Recordings 32 3.3 Artificial Mixtures 36 3.4 Impulse Response Models 37 3.5 Summary 43 Bibliography 43 4 Multichannel Source Activity Detection, Localization, and Tracking 47Pasi Pertilä, Alessio Brutti, Piergiorgio Svaizer, and Maurizio Omologo 4.1 Basic Notions in Multichannel Spatial Audio 47 4.2 Multi-Microphone Source Activity Detection 52 4.3 Source Localization 54 4.4 Summary 60 Bibliography 60 Part II Single-Channel Separation and Enhancement 655 Spectral Masking and Filtering 67Timo Gerkmann and Emmanuel Vincent 5.1 Time-Frequency Masking 67 5.2 Mask Estimation Given the Signal Statistics 70 5.3 Perceptual Improvements 81 5.4 Summary 82 Bibliography 83 6 Single-Channel Speech Presence Probability Estimation and Noise Tracking 87Rainer Martin and Israel Cohen 6.1 Speech Presence Probability and its Estimation 87 6.2 Noise Power Spectrum Tracking 93 6.3 Evaluation Measures 102 6.4 Summary 104 Bibliography 104 7 Single-Channel Classification and Clustering Approaches 107FelixWeninger, Jun Du, Erik Marchi, and Tian Gao 7.1 Source Separation by Computational Auditory Scene Analysis 108 7.2 Source Separation by Factorial HMMs 111 7.3 Separation Based Training 113 7.4 Summary 125 Bibliography 125 8 Nonnegative Matrix Factorization 131Roland Badeau and Tuomas Virtanen 8.1 NMF and Source Separation 131 8.2 NMF Theory and Algorithms 137 8.3 NMF Dictionary LearningMethods 145 8.4 Advanced NMF Models 148 8.5 Summary 156 Bibliography 156 9 Temporal Extensions of Nonnegative Matrix Factorization 161Cédric Févotte, Paris Smaragdis, NasserMohammadiha, and Gautham J.Mysore 9.1 Convolutive NMF 161 9.2 Overview of DynamicalModels 169 9.3 Smooth NMF 170 9.4 Nonnegative State-Space Models 174 9.5 Discrete DynamicalModels 178 9.6 The Use of DynamicModels in Source Separation 182 9.7 Which Model to Use? 183 9.8 Summary 184 9.9 Standard Distributions 184 Bibliography 185 Part III Multichannel Separation and Enhancement 189 10 Spatial Filtering 191Shmulik Markovich-Golan,Walter Kellermann, and Sharon Gannot 10.1 Fundamentals of Array Processing 192 10.2 Array Topologies 197 10.3 Data-Independent Beamforming 199 10.4 Data-Dependent Spatial Filters: Design Criteria 202 10.5 Generalized Sidelobe Canceler Implementation 209 10.6 Postfilters 210 10.7 Summary 211 Bibliography 212 11 Multichannel Parameter Estimation 219Shmulik Markovich-Golan,Walter Kellermann, and Sharon Gannot 11.1 Multichannel Speech Presence Probability Estimators 219 11.2 Covariance Matrix Estimators Exploiting SPP 227 11.3 Methods forWeakly Guided and Strongly Guided RTF Estimation 228 11.4 Summary 231 Bibliography 231 12 Multichannel Clustering and Classification Approaches 235Michael I.Mandel, Shoko Araki, and Tomohiro Nakatani 12.1 Two-Channel Clustering 236 12.2 Multichannel Clustering 244 12.3 Multichannel Classification 251 12.4 Spatial Filtering Based on Masks 255 12.5 Summary 257 Bibliography 258 13 Independent Component and Vector Analysis 263Hiroshi Sawada and Zbynˇek Koldovský 13.1 Convolutive Mixtures and their Time-Frequency Representations 264 13.2 Frequency-Domain Independent Component Analysis 265 13.3 Independent Vector Analysis 279 13.4 Example 280 13.5 Summary 284 Bibliography 284 14 Gaussian Model Based Multichannel Separation 289Alexey Ozerov and Hirokazu Kameoka 14.1 Gaussian Modeling 289 14.2 Library of Spectral and SpatialModels 295 14.3 Parameter Estimation Criteria and Algorithms 300 14.4 Detailed Presentation of Some Methods 305 14.5 Summary 312 Acknowledgment 312 Bibliography 312 15 Dereverberation 317Emanuël A.P. Habets and Patrick A. Naylor 15.1 Introduction to Dereverberation 317 15.2 Reverberation Cancellation Approaches 319 15.3 Reverberation Suppression Approaches 329 15.4 Direct Estimation 335 15.5 Evaluation of Dereverberation 336 15.6 Summary 337 Bibliography 337 Part IV Application Scenarios and Perspectives 345 16 Applying Source Separation to Music 347Bryan Pardo, Antoine Liutkus, Zhiyao Duan, and Gaël Richard 16.1 Challenges and Opportunities 348 16.2 Nonnegative Matrix Factorization in the Case of Music 349 16.3 Taking Advantage of the Harmonic Structure of Music 354 16.4 Nonparametric Local Models: Taking Advantage of Redundancies in Music 358 16.5 Taking Advantage of Multiple Instances 363 16.6 Interactive Source Separation 367 16.7 Crowd-Based Evaluation 367 16.8 Some Examples of Applications 368 16.9 Summary 370 Bibliography 370 17 Application of Source Separation to Robust Speech Analysis and Recognition 377ShinjiWatanabe, Tuomas Virtanen, and Dorothea Kolossa 17.1 Challenges and Opportunities 377 17.2 Applications 380 17.3 Robust Speech Analysis and Recognition 390 17.4 Integration of Front-End and Back-End 397 17.5 Use of Multimodal Information with Source Separation 403 17.6 Summary 404 Bibliography 405 18 Binaural Speech Processing with Application to Hearing Devices 413Simon Doclo, Sharon Gannot, Daniel Marquardt, and Elior Hadad 18.1 Introduction to Binaural Processing 413 18.2 Binaural Hearing 415 18.3 Binaural Noise Reduction Paradigms 416 18.4 The Binaural Noise Reduction Problem 420 18.5 Extensions for Diffuse Noise 425 18.6 Extensions for Interfering Sources 431 18.7 Summary 437 Bibliography 437 19 Perspectives 443Emmanuel Vincent, Tuomas Virtanen, and Sharon Gannot 19.1 Advancing Deep Learning 443 19.2 Exploiting Phase Relationships 447 19.3 AdvancingMultichannel Processing 450 19.4 Addressing Multiple-Device Scenarios 453 19.5 TowardsWidespread Commercial Use 455 Acknowledgment 457 Bibliography 457 Index 465

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Book SynopsisPhotovoltaic Power System: Modelling, Design and Control is an essential reference with a practical approach to photovoltaic (PV) power system analysis and control. It systematically guides readers through PV system design, modelling, simulation, maximum power point tracking and control techniques making this invaluable resource to students and professionals progressing from different levels in PV power engineering. The development of this book follows the author''s 15-year experience as an electrical engineer in the PV engineering sector and as an educator in academia. It provides the background knowledge of PV power system but will also inform research direction. Key features: Details modern converter topologies and a step-by-step modelling approach to simulate and control a complete PV power system. Introduces industrial standards, regulations, and electric codes for safety practice and research direction. Covers new classificatTrade Review�This book is an excellent explanation of PV power systems and its controls. It brings sufficient knowledge on modeling and designing different kinds of PV systems (both standalone and grid-tied). In the first 4 chapters, it focuses more on the introduction and PV basics such as PV classification, characteristics, and mathematical models. This information will lead readers to a general understanding of PV fundamentals, providing a smooth transition from basic knowledge to advanced industrial PV applications. It perfectly combines the theory and practical exercises. In chapter 5, it discusses the design, simulates and evaluates of state-of-art system components such as PV-side converters, battery-side converters, and grid-side converters. After discussing the system components, in the next two chapters, the complete dynamic modeling of PV systems are introduced. This book emphasizes the computer-aided analysis and simulation verification. The detailed equations behind the functions are provided, and the simulation blocks used are built using the commonly used blocks in Simulink. Readers can easily follow the step-by-step instructions to simulate the whole PV system in Matlab. Apart from system modeling, the control of the entire PV system like linear control and MPPT technology are also addressed. This book fulfills important demand in both academia and industry. It is also a perfect choice to support teaching senior-undergraduate and graduate courses.� • Dr. Yang Du, Xi�an Jiaotong – Liverpool University �This is a textbook for a course that would appear to be suitable for upper level graduate students. It could also be used by undergraduates and master�s degree level students who want to get a general idea of how solar electric power systems work. The book reads well and should be accessible to most college students and certainly almost all graduate students. In addition to its use for higher education, this book could be used by engineers and utility executives who want to understand the technology of solar photovoltaic systems�It is possible to contemplate using this book to learn about and to teach about solar photovoltaic systems. This is clearly a textbook: it is not a design reference book. With increasing importance of sustainable sources of electric power, there is a clear need to better educate university students about the technology of photovoltaic power. This book should make a serious contribution.� • James Kirtley, Professor of Electrical Engineering, Massachusetts Institute of Technology �This book is an excellent choice for beginners working in the photovoltaic industry. It contains a nice mix of industrial applications/examples along with theoretical derivations of photovoltaic system at component- and system-level. The step-by-step discussion on industry background, problem formulation, mathematical modelling, computer simulation, and practical implementation provides a holistic view of designing photovoltaic systems. Detailed simulations modelling the dynamics of individual photovoltaic cell, maximum power point tracking, energy conversion (DC-DC and DC-AC), and grid-level auxiliary services (such as voltage regulation) are also provided. Since the designed MATLAB/SIMULINK block diagrams are provided throughout this book, reproducing the waveforms and results are feasible. In my opinion, this is the most important element� The addition of this book helps students and researchers to quickly grasp the fundamentals of photovoltaic systems. Note that the materials covered in this book are more suitable for graduate students.� • Jimmy C.-H. Peng, Assistant Professor, Department of Electrical & Computer Engineering, National University of Singapore �This book provides an inclusive introduction to the field of photovoltaic systems. It covers the basics of PV systems, their classifications, modeling, practical design issues, and their control and operation. It provides in-depth discussions for several modeling and control issues of PV systems and their power electronic converters. The book can be used to help students and researchers gain knowledge on the state of the art in this area and can familiarize engineers with designing safe and practical PV systems. I use the book as a textbook for the graduate course I teach at Worcester Polytechnic Institute about photovoltaic power systems. I found it the most comprehensive book that covers wide areas in PV engineering.� • Yousef A. Mahmoud, Assistant Professor, Worcester Polytechnic InstituteTable of ContentsPreface xiii Acknowledgments xvii About the companion website xix 1 Introduction 1 1.1 Cell, Module, Panel, String, Subarray, and Array 2 1.2 Blocking Diode 5 1.3 Photovoltaic Cell Materials and Efficiency 6 1.4 Test Conditions 7 1.5 PV Module Test 8 1.6 PV Output Characteristics 9 1.7 PV Array Simulator 12 1.8 Power Interfaces 13 1.9 Standalone Systems 13 1.10 AC Grid-connected Systems 18 1.11 DC Grid and Microgrid Connections 19 1.12 Building-integrated Photovoltaics 21 1.13 Other Solar Power Systems 22 1.14 Sun Trackers 23 Problems 24 References 24 2 Classification of Photovoltaic Power Systems 25 2.1 Background 25 2.2 CMPPT Systems 26 2.2.1 Power Loss due to PV Array Mismatch 29 2.2.2 Communication and Data Acquisition for CMPPT Systems 32 2.3 DMPPT Systems at PV String Level 36 2.4 DMPPT Systems at PV Module Level 37 2.4.1 Module-integrated Parallel Inverters 37 2.4.2 Module-integrated Parallel Converters 39 2.4.3 Module-integrated Series Converters 40 2.4.4 Module-integrated Differential Power Processors 40 2.4.5 Module-integrated Series Inverters 41 2.5 DMPPT Systems at PV Submodule Level 42 2.5.1 Submodule-integrated Series Converters 42 2.5.2 Submodule-integrated Differential Power Processors 43 2.5.3 Isolated-port Differential Power Processors 44 2.6 DMPPT Systems at PV Cell Level 44 2.7 Summary 45 Problems 46 References 46 3 Safety Standards, Guidance and Regulation 49 3.1 Certification of PV Modules 49 3.2 Interconnection Standards 51 3.3 System Integration to Low-voltage Networks 55 3.3.1 Grounded Systems 55 3.3.2 DC Ground Fault Protection 56 3.3.3 Voltage Specification 56 3.3.4 Circuit Sizing and Current 58 3.3.5 Cable Selection 58 3.3.6 Connectors and Disconnects 59 3.3.7 Grid Interconnections through Power Distribution Panels 59 3.3.8 Marking 60 3.4 System Integration to Medium-voltage Network 60 3.4.1 Active Power Throttling 61 3.4.2 Fault Ride-through 61 3.4.3 Reactive Power Support 62 3.5 Summary 63 Problems 63 References 64 4 PV Output Characteristics and Mathematical Models 65 4.1 Ideal Single-diode Model 68 4.1.1 Product Specification 68 4.1.2 Parameter Identification at Standard Test Conditions 69 4.1.3 Variation with Irradiance and Temperature 71 4.2 Model Accuracy and Performance Indices 75 4.3 Simplified Single-diode Models 78 4.3.1 Parameter Identification: Part One 79 4.3.2 Parameter Identification: Part Two 81 4.3.3 Variation with Irradiance and Temperature 87 4.4 Model Selection from the Simplified Single-diode Models 88 4.5 Complete Single-diode Model 91 4.6 Model Aggregation and Terminal Output Configuration 92 4.7 Polynomial Curve Fitting 95 4.8 Summary 99 Problems 100 References 101 5 Power Conditioning 103 5.1 PV-side Converters 104 5.1.1 PV Module for Case Study 105 5.1.2 Buck Converter 105 5.1.3 Full-bridge Isolated Transformer DC/DC Converter 110 5.1.4 Boost Converter 115 5.1.5 Tapped-inductor Boost Topology 119 5.1.6 Buck–Boost Converter 122 5.1.7 Flyback Converter 126 5.2 Battery-side Converter for DC/DC Stage 130 5.2.1 Introduction to Dual Active Bridges 130 5.2.2 Discharge Operation 131 5.2.3 Charging Operation 135 5.2.4 Zero Voltage Switching 139 5.3 DC Link 142 5.3.1 DC Link for Single-phase Grid Interconnection 143 5.3.2 DC Link for Three-phase Grid Interconnections 145 5.4 Grid-side Converter for DC/AC Stage 147 5.4.1 DC to Single-phase AC Grid 147 5.4.2 DC to Three-phase AC Grid 151 5.4.3 Reactive Power 153 5.5 Grid Link 154 5.5.1 L-type for Single-phase Grid Connections 154 5.5.2 L-type for Three-phase Grid Interconnections 155 5.5.3 LCL-type Filters 157 5.5.4 LC-type Filters 160 5.6 Loss Analysis 160 5.6.1 Conduction Loss 161 5.6.2 High-frequency Loss 163 5.7 Conversion Efficiency 165 5.8 Wide Band-gap Devices for Future Power Conversion 165 5.9 Summary 167 Problems 169 References 171 6 Dynamic Modeling 173 6.1 State-space Averaging 173 6.2 Linearization 174 6.3 Dynamics of PV Link 175 6.3.1 Linearization of PV Output Characteristics 175 6.3.2 Buck Converter as the PV-link Power Interface 176 6.3.3 Full-bridge Transformer Isolated DC/DC as the PV-link Power Interface 180 6.3.4 Boost Converter as the PV-link Power Interface 182 6.3.5 Tapped-inductor Topology as the PV-link Power Interface 184 6.3.6 Buck–boost Converter as the PV-link Power Interface 186 6.3.7 Flyback Converter as the PV-link power Interface 188 6.4 Dynamics of DC Bus Voltage Interfaced with Dual Active Bridge 189 6.5 Dynamics of DC Link for AC Grid Connection 192 6.5.1 Single-phase Connection 192 6.5.2 Three-phase Connection 194 6.6 Summary 195 Problems 196 References 197 7 Voltage Regulation 199 7.1 Structure of Voltage Regulation in Grid-connected PV Systems 199 7.2 Affine Parameterization 201 7.3 PID-type Controllers 202 7.4 Desired Performance in Closed Loop 205 7.5 Relative Stability 206 7.6 Robustness 208 7.7 Feedforward Control 209 7.8 Voltage Regulation in PV Links 210 7.8.1 Boost Converter for PV Links 210 7.8.2 Tapped-inductor Topology for PV Links 213 7.8.3 Buck Converter as the PV-link Power Interface 214 7.8.4 Buck–boost Converter as the PV-link Power Interface 216 7.8.5 Flyback Converter as the PV-link Converter 218 7.9 Bus Voltage Regulation for DC Microgrids 220 7.10 DC-link Voltage Regulation for AC Grid Interconnections 221 7.10.1 Single-phase Grid Interconnection 222 7.10.2 Three-phase Grid Interconnection 226 7.11 Sensor, Transducer, and Signal Conditioning 227 7.12 Anti-windup 230 7.13 Digital Control 236 7.13.1 Continuous Time and Discrete Time 240 7.13.2 Digital Redesign 240 7.13.3 Time Delay due to Digital Conversion and Process 243 7.14 Summary 245 Problems 246 References 247 8 Maximum Power Point Tracking 249 8.1 Background 249 8.2 Heuristic Search 252 8.3 Extreme-value Searching 255 8.4 Sampling Frequency and Perturbation Size 257 8.5 Case Study 258 8.6 Start-stop Mechanism for HC-based MPPT 261 8.7 Adaptive Step Size Based on the Steepest Descent 264 8.8 Centered Differentiation 267 8.9 Real-time System Identification 270 8.9.1 Recursive Least Squares Method 270 8.9.2 Newton–Raphson Method for MPP Determination 272 8.9.3 Forgetting Factor 272 8.10 Extremum Seeking 273 8.11 Multiple Power Peaks and Global MPPT 276 8.12 Performance Evaluation of MPPT 277 8.12.1 Review of Indoor Test Environment 277 8.12.2 Review of Outdoor Test Environments 278 8.12.3 Recommended Test Benches for MPPT Evaluation 279 8.12.4 Statistical Paired Differential Evaluation 280 8.13 Summary 281 Problems 283 References 284 9 Battery Storage and Standalone System Design 285 9.1 Batteries 287 9.1.1 Battery Types 288 9.1.2 Battery Terminology 291 9.1.3 Charging Methods 292 9.1.4 Battery Mismatches and Balancing Methods 295 9.1.5 Battery Characteristics and Modeling 300 9.1.6 Battery Selection 308 9.2 Integrating Battery-charge Control with MPPT 308 9.3 Design of Standalone PV Systems 309 9.3.1 Systems without Significant Energy Storage 309 9.3.2 Systems with Significant Energy Storage 311 9.4 Equivalent Circuit for Simulation and Case Study 316 9.5 Simulation Model to Integrate Battery-charging with MPPT 317 9.6 Simulation Study of Standalone Systems 318 9.6.1 Simulation of PV Array 318 9.6.2 Short-term Simulation 319 9.6.3 Medium-term Simulation 321 9.6.4 Long-term Simulations 325 9.6.5 Very-long-term Simulations 328 9.7 Summary 329 Problems 331 References 332 10 System Design and Integration of Grid-connected Systems 333 10.1 System Integration of Single-phase Grid-connected System 335 10.1.1 Distributed Maximum Power Point Tracking at String Level 335 10.1.2 Distributed Maximum Power Point Tracking at PV Module Level 337 10.2 Design Example of Three-phase Grid-connected System 340 10.3 System Simulation and Concept Proof 343 10.3.1 Modeling and Simulation of PV String 344 10.3.2 Modeling and Simulation of DC/DC Stage 345 10.3.3 Modeling and Simulation of DC/AC Stage 349 10.3.4 Overall System Integration and Simulation 351 10.4 Simulation Efficiency for Conventional Grid-connected PV Systems 351 10.4.1 Averaging Technique for Switching-mode Converters 353 10.4.2 Overall System Integration and Simulation 354 10.4.3 Long-term Simulation 357 10.5 Grid-connected System Simulation Based on Module Integrated Parallel Inverters 359 10.5.1 Averaged Model for Module-integrated Parallel Inverters 359 10.5.2 Overall System Integration and Simulation 362 10.6 Summary 365 Problems 366 References 366 Index 367

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Book SynopsisThis is a pioneering textbook on the comprehensive description of AeroMACS technology. It alsopresents the process of developing a new technology based on an established standard, in this case IEEE802.16 standards suite. The text introduces readers to the field of airport surface communications systems and provides them with comprehensive coverage of one the key components of the Next Generation Air Transportation System (NextGen); i.e., AeroMACS. It begins with a critical review of the legacy aeronautical communications system and a discussion of the impetus behind its replacement with network-centric digital technologies. It then describes wireless mobile channel characteristics in general, and focuses on the airport surface channel over the 5GHz band. This is followed by an extensive coverage of major features of IEEE 802.16-2009 Physical Layer (PHY)and Medium Access Control (MAC) Sublayer. The text then provides a comprehensive coverage of the AeroMACS standTable of ContentsPreface xvii Acronyms xxv 1 Airport Communications from Analog AM to AeroMACS 1 1.1 Introduction 1 1.2 Conventional Aeronautical Communication Domains (Flight Domains) 2 1.3 VHF Spectrum Depletion 4 1.4 The ACAST Project 5 1.5 Early Digital Communication Technologies for Aeronautics 7 1.5.1 ACARS 7 1.5.2 VHF Data Link (VDL) Systems 8 1.5.2.1 Aeronautical Telecommunications Network (ATN) 8 1.5.2.2 VDL Systems 8 1.5.3 Overlay Broadband Alternatives for Data Transmission 10 1.5.3.1 Direct-Sequence Spread Spectrum Overlay 11 1.5.3.2 Broadband VHF (B-VHF) 11 1.5.4 Controller–Pilot Data Link Communications (CPDLC) 12 1.6 Selection of a Communications Technology for Aeronautics 14 1.7 The National Airspace System (NAS) 15 1.7.1 Flight Control 16 1.7.2 United States Civilian Airports 17 1.8 The Next Generation Air Transportation System (NextGen) 20 1.8.1 The NextGen Vision 22 1.8.2 NextGen Key Components and Functionalities 22 1.9 Auxiliary Wireless Communications Systems Available for the Airport Surface 25 1.9.1 Public Safety Mobile Radio for Airport Incidents 26 1.9.1.1 Public Safety Communications (PSC) Systems Architecture and Technologies 26 1.9.1.2 Public Safety Allocated Radio Spectrum 27 1.9.1.3 700 MHz Band and the First Responder Network Authority (FirstNet) 28 1.9.2 Wireless Fidelity (WiFi) Systems Applications for Airport Surface 30 1.10 Airport Wired Communications Systems 31 1.10.1 Airport Fiber-Optic Cable Loop System 34 1.10.2 Applications of CLCS in Airport Surface Communications and Navigation 35 1.11 Summary 36 References 36 2 Cellular Networking and Mobile Radio Channel Characterization 41 2.1 Introduction 41 2.2 The Crux of the Cellular Concept 42 2.2.1 The “Precellular” Wireless Mobile Communications Systems 43 2.2.2 The Core of the Cellular Notion 45 2.2.3 Frequency Reuse and Radio Channel Multiplicity 48 2.2.3.1 Co-Channel Reuse Ratio (CCRR), Cluster Size, and Reuse Factor 49 2.2.3.2 Signal to Co-Channel Interference Ratio (SIR) 50 2.2.3.3 Channel Allocation 55 2.2.4 Erlang Traffic Theory and Cellular Network Design 57 2.2.4.1 Trunking, Erlang, and Traffic 58 2.2.4.2 The Grade of Service 60 2.2.4.3 Blocked Calls Handling Strategies 60 2.2.4.4 Trunking Efficiency 62 2.2.4.5 Capacity Enhancement through Cell Splitting 64 2.2.4.6 Capacity Enhancement via Sectorization 67 2.3 Cellular Radio Channel Characterization 69 2.3.1 Cellular Link Impairments 69 2.3.2 Path Loss Computation and Estimation 71 2.3.2.1 Free-Space Propagation and Friis Formula 73 2.3.2.2 The Key Mechanisms Affecting Radio Wave Propagation 74 2.3.2.3 The Ray Tracing Technique 76 2.3.2.4 Ground Reflection and Double-Ray Model 76 2.3.2.5 Empirical Techniques for Path Loss (Large-Scale Attenuation) Estimation 81 2.3.2.6 Okumura–Hata Model for Outdoor Median Path Loss Estimation 82 2.3.2.7 COST 231-Hata Model 84 2.3.2.8 Stanford University Interim (SUI) Model: Erceg Model 85 2.3.2.9 ECC-33 Model 86 2.3.3 Large-Scale Fading: Shadowing and Foliage 87 2.3.3.1 Log-Normal Shadowing 88 2.3.3.2 Estimation of Useful Coverage Area (UCA) within a Cell Footprint 91 2.3.4 Small-Scale Fading: Multipath Propagation and Doppler Effect 94 2.3.4.1 Multipath Propagation 95 2.3.4.2 Double Path Example 97 2.3.4.3 Doppler Shift 99 2.3.4.4 Impulse Response of Multipath Channels 100 2.3.4.5 Delay Spread and Fading Modes 102 2.3.4.6 Methods of Combating Frequency-Selective Fading 103 2.3.4.7 Coherence Bandwidth and Power Delay Profiles (PDPs) 105 2.3.4.8 Frequency Flat Fading versus Frequency-Selective Fading 108 2.3.4.9 Frequency Dispersion and Coherence Time 109 2.3.4.10 Classification of Multipath Fading Channels 110 2.3.4.11 Probabilistic Models for Frequency Flat Fading Channels 112 2.3.4.12 Rayleigh Fading Channels 112 2.3.4.13 Rician Fading Channels 115 2.4 Challenges of Broadband Transmission over the Airport Surface Channel 117 2.5 Summary 118 References 119 3 Wireless Channel Characterization for the 5 GHz Band Airport Surface Area 123 3.1 Introduction 123 3.1.1 Importance of Channel Characterization 123 3.1.2 Channel Definitions 125 3.1.3 Airport Surface Area Channel 127 3.2 Statistical Channel Characterization Overview 129 3.2.1 The Channel Impulse Response and Transfer Function 129 3.2.2 Statistical Channel Characteristics 130 3.2.3 Common Channel Parameters and Statistics 133 3.3 Channel Effects and Signaling 134 3.3.1 Small-Scale and Large-Scale Fading 134 3.3.2 Channel Parameters and Signaling Relations 135 3.4 Measured Airport Surface Area Channels 137 3.4.1 Measurement Description and Example Results 137 3.4.2 Path Loss Results 141 3.5 Airport Surface Area Channel Models 143 3.5.1 Large/Medium-Sized Airports 144 3.5.2 Small Airports 144 3.6 Summary 144 References 147 4 Orthogonal Frequency-Division Multiplexing and Multiple Access 151 4.1 Introduction 151 4.2 Fundamental Principles of OFDM Signaling 152 4.2.1 Parallel Transmission, Orthogonal Multiplexing, Guard Time, and Cyclic Extension 154 4.2.1.1 Cyclic Prefix and Guard Time 155 4.2.2 Fourier Transform-Based OFDM Signal 156 4.2.3 Windowing, Filtering, and Formation of OFDM Signal 157 4.2.4 OFDM System Implementation 159 4.2.5 Choice of Modulation Schemes for OFDM 160 4.2.6 OFDM Systems Design: How the Key Parameters are Selected 161 4.3 Coded Orthogonal Frequency-Division Multiplexing: COFDM 161 4.3.1 Motivation 162 4.3.2 System-Level Functional Block Diagram of a Fourier-Based COFDM 162 4.3.3 Some Classical Applications of COFDM 164 4.3.3.1 COFDM Applied in Digital Audio Broadcasting (DAB) 164 4.3.3.2 COFDM Applied in Wireless LAN (Wi-Fi): The IEEE 802.11 Standard 165 4.4 Performance of Channel Coding in OFDM Networks 167 4.5 Orthogonal Frequency-Division Multiple Access: OFDMA 169 4.5.1 Multiple Access Technologies: FDMA, TDMA, CDMA, and OFDMA 171 4.5.2 Incentives behind Widespread Applications of OFDMA in Wireless Networks 175 4.5.3 Subchannelization and Symbol Structure 176 4.5.4 Permutation Modes for Configuration of Subchannels 178 4.5.4.1 The Peak-to-Average Power Ratio Problem 179 4.6 Scalable OFDMA (SOFDMA) 179 4.6.1 How to Select the OFDMA Basic Parameters vis-à-vis Scalability 180 4.6.2 Options in Scaling 182 4.7 Summary 183 References 184 5 The IEEE 802.16 Standards and the WiMAX Technology 189 5.1 Introduction to the IEEE 802.16 Standards for Wireless MAN Networks 190 5.2 The Evolution and Characterization of IEEE 802.16 Standards 193 5.2.1 IEEE 802.16-2004 Standard 193 5.2.2 IEEE 802.16e-2005 Standard 194 5.2.3 IEEE 802.16-2009 Standard 194 5.2.4 IEEE 802.16j Amendment 194 5.2.5 The Structure of a WirelessMAN Cell 195 5.2.6 Protocol Reference Model (PRM) for the IEEE 802.16-2009 Standard 197 5.3 WiMAX: an IEEE 802.16-Based Technology 200 5.3.1 Basic Features of WiMAX Systems 200 5.3.2 WiMAX Physical Layer Characterization 204 5.3.2.1 OFDMA and SOFDMA for WiMAX 205 5.3.2.2 Comparison of Duplexing Technologies: TDD versus FDD 206 5.3.2.3 Subchannelization for Mobile WiMAX 207 5.3.2.4 WiMAX TDD Frame Structure 211 5.3.2.5 Adaptive (Advanced) Modulation and Coding (AMC) 215 5.3.2.6 ARQ and Hybrid ARQ: Multilayer Error Control Schemes 219 5.3.2.7 Multiple Antenna Techniques, MIMO, and Space-Time Coding 219 5.3.2.8 Fractional Frequency Reuse Techniques for Combating Intercell Interference and to Boost Spectral Efficiency 227 5.3.2.9 Power Control and Saving Modes in WiMAX Networks 230 5.3.3 WiMAX MAC Layer Description 231 5.3.3.1 WiMAX MAC CS; Connections and Service Flows 232 5.3.3.2 The MAC CPS Functionalities 232 5.3.3.3 WiMAX Security Sublayer 233 5.3.3.4 WiMAX MAC Frame and MAC Header Format 234 5.3.3.5 Quality of Service (QoS), Scheduling, and Bandwidth Allocation 235 5.3.4 WiMAX Forum and WiMAX Profiles 239 5.3.4.1 WiMAX System Profiles and Certification Profiles 240 5.3.4.2 WiMAX Mobile System Profiles 241 5.3.5 WiMAX Network Architecture 245 5.3.5.1 WiMAX Network Reference Model as Presented by WiMAX Forum 246 5.3.5.2 Characterization of Major Logical and Physical Components of WiMAX NRM 248 5.3.5.3 Visual Depiction of WiMAX NRM 250 5.3.5.4 The Description of WiMAX Reference Points 250 5.3.6 Mobility and Handover in WiMAX Networks 250 5.3.7 Multicast and Broadcast with WiMAX 253 5.4 Summary 254 References 255 6 Introduction to AeroMACS 259 6.1 The Origins of the AeroMACS Concept 259 6.1.1 WiMAX Salient Features and the Genealogy of AeroMACS 260 6.2 Defining Documents in the Making of AeroMACS Technology 262 6.3 AeroMACS Standardization 267 6.3.1 AeroMACS Standards and Recommended Practices (SARPS) 268 6.3.2 Harmonization Document 270 6.3.3 Overview of Most Recent AeroMACS Profile 271 6.3.3.1 The AeroMACS Profile Background and Concept of Operations 273 6.3.3.2 AeroMACS Profile Technical Aspects 275 6.3.3.3 Profile’s Key Assumptions for AeroMACS System Design 275 6.3.3.4 AeroMACS Radio Profile Requirements and Restrictions 276 6.3.3.5 AeroMACS Profile Common Part and TDD Format 277 6.3.4 AeroMACS Minimum Operational Performance Standards (MOPS) 279 6.3.4.1 AeroMACS Capabilities and Operational Applications 280 6.3.4.2 MOPS Equipment Test Procedures 281 6.3.4.3 Minimum Performance Standard 281 6.3.5 AeroMACS Minimum Aviation System Performance Standards (MASPS) 283 6.3.6 AeroMACS Technical Manual 285 6.4 AeroMACS Services and Applications 287 6.5 AeroMACS Prototype Network and Testbed 295 6.5.1 Testbed Configuration 296 6.5.2 Early Testing Procedures and Results 297 6.5.2.1 Mobile Application Testing with ARV 298 6.5.2.2 The Results of AeroMACS Mobile Tests with Boeing 737–700 299 6.5.2.3 AeroMACS Performance Validation 300 6.6 Summary 301 References 302 7 AeroMACS Networks Characterization 305 7.1 Introduction 305 7.2 AeroMACS Physical Layer Specifications 306 7.2.1 OFDM and OFDMA for AeroMACS 309 7.2.2 AeroMACS OFDMA TDD Frame Configuration 309 7.2.3 AeroMACS Modulation Formats 312 7.2.3.1 How to Select a Modulation Technique for a Specific Application 313 7.2.3.2 General Characteristics of Modulation Schemes Supported by AeroMACS 315 7.2.4 AeroMACS Channel Coding Schemes 318 7.2.4.1 Mandatory Channel Coding for AeroMACS 318 7.2.4.2 Optional CC–RS Code Concatenated Scheme 320 7.2.4.3 Convolutional Turbo Coding (CTC) Technique 321 7.2.5 Adaptive Modulation and Coding (AMC) for AeroMACS Link Adaptation 323 7.2.6 AeroMACS Frame Structure 325 7.2.7 Computation of AeroMACS Receiver Sensitivity 326 7.2.8 Fractional Frequency Reuse for WiMAX and AeroMACS Networks 327 7.2.9 Multiple-Input Multiple-Output (MIMO) Configurations for AeroMACS 328 7.3 Spectrum Considerations 329 7.4 Spectrum Sharing and Interference Compatibility Constraints 332 7.5 AeroMACS Media Access Control (MAC) Sublayer 334 7.5.1 Quality of Service for AeroMACS Networks 336 7.5.2 Scheduling, Resource Allocation, and Data Delivery 338 7.5.3 Automatic Repeat Request (ARQ) Protocols 341 7.5.4 Handover (HO) Procedures in AeroMACS Networks 344 7.5.4.1 MS-Initiated Handover Process 345 7.6 AeroMACS Network Architecture and Reference Model 347 7.6.1 AeroMACS Network Architecture 347 7.6.2 AeroMACS Network Reference Model (NRM) 349 7.7 Aeronautical Telecommunications Network Revisited 353 7.8 AeroMACS and the Airport Network 355 7.9 Summary 356 References 358 8 AeroMACS Networks Fortified with Multihop Relays 361 8.1 Introduction 361 8.2 IEEE 802.16j Amendment Revisited 362 8.3 Relays: Definitions, Classification, and Modes of Operation 365 8.3.1 A Double-Hop Relay Configuration: Terminologies and Definitions 366 8.3.2 Relay Modes: Transparent versus Non-Transparent 368 8.3.3 Time Division Transmit and Receive Relays (TTR) and Simultaneous Transmit and Receive Relays (STR) 371 8.3.4 Further Division of Relay Modes of Operation 372 8.3.5 Relays Classification Based on MAC Layer Functionalities: Centralized and Distributed Modes 373 8.3.6 Physical Classification of IEEE 802.16j Relays: Relay Types 374 8.3.6.1 Relay Type and Latency 375 8.3.7 Modes of Deployment of IEEE 802.16j Relays in Wireless Networks 376 8.3.8 Frame Structure for Double-Hop IEEE 802.16j TDD TRS 377 8.3.8.1 The Detail of IEEE 802-16j Operation with Transparent Relays 380 8.3.9 The Frame Structure for TTR–NTRS 381 8.3.10 The Frame Structure for STR–NTRS 382 8.3.10.1 STR Implementation in Different Layers 384 8.4 Regarding MAC Layers of IEEE 802.16j and NRTS 385 8.4.1 Data Forwarding Schemes 385 8.4.1.1 Routing Selection and Path Management 386 8.4.1.2 Initial Ranging and Network Entry 387 8.4.2 Scheduling 388 8.4.3 Security Schemes 390 8.4.4 Quality of Service (QoS) in Relay-Augmented Networks 390 8.4.4.1 The Impact of Scheduling and Relay Mode on AeroMACS Network Parameters 391 8.5 Challenges and Practical Issues in IEEE 802.16j-Based AeroMACS 392 8.5.1 Latency 392 8.5.2 The Number of Hops 392 8.5.3 The Output Power and Antenna Selection 393 8.6 Applications and Usage Scenarios for Relay-Augmented Broadband Cellular Networks 394 8.6.1 Some Applications of Relay-Fortified Systems 395 8.6.1.1 The European REWIND Project 395 8.6.1.2 Vehicular Networks 396 8.6.1.3 4G and 5G Cellular Networks 396 8.6.1.4 Cognitive Femtocell 397 8.6.2 Potential Usage Scenarios of IEEE 802.16j 397 8.6.2.1 Radio Outreach Extension 397 8.6.2.2 The Concept of “Filling a Coverage Hole” 399 8.6.2.3 Relays for Capacity and Throughput Improvement 399 8.6.2.4 The Case of Cooperative Relaying 399 8.6.2.5 Reliable Coverage for In-Building and In-Door Scenarios 400 8.6.2.6 The Mobile Relays 401 8.6.2.7 The Temporary Relay Stations 401 8.7 IEEE 802.16j-Based Relays for AeroMACS Networks 401 8.7.1 Airport Surface Radio Coverage Situations for which IEEE 802.16j Offers a Preferred Alternative 402 8.8 Radio Resource Management (RRM) for Relay-Fortified Wireless Networks 403 8.9 The Multihop Gain 405 8.9.1 Computation of Multihop Gain for the Simplest Case 405 8.10 Interapplication Interference (IAI) in Relay-Fortified AeroMACS 407 8.11 Making the Case for IEEE 802.16j-Based AeroMACS 411 8.11.1 The Main Arguments 411 8.11.1.1 Supporting and Drawback Instants 412 8.11.2 The Second Argument 412 8.11.3 How to Select a Relay Configuration 413 8.11.4 A Note on Cell Footprint Extension 413 8.12 Summary 414 References 415 Index 419

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Book SynopsisA comprehensive reference to renewable energy technologies with a focus on power generation and integration into power systems This book addresses the generation of energy (primarily electrical) through various renewable sources.Table of ContentsPreface xvii 1 Sources of Energy and Technologies 1 1.1 Energy Uses in Different Countries 1 1.2 Energy Sources 3 1.2.1 Non-Renewable Energy Resources 3 1.2.2 Renewable Sources of Energy 3 1.3 Energy and Environment 5 1.3.1 Climate Change 7 1.4 Review of Technologies for Renewable Energy System 8 1.4.1 Fluid Dynamics 8 1.4.1.1 Conservation of Mass 8 1.4.1.2 Conservation of Momentum 9 1.4.1.3 Conservation of Energy 10 1.5 Thermodynamics 11 1.5.1 Enthalpy 12 1.5.2 Specific Heat 12 1.5.3 Zeroth Law 13 1.5.4 First Law 13 1.5.4.1 Limitations of First law 14 1.5.5 Second Law of Thermodynamics 14 1.5.5.1 Kelvin–Planck Statement 15 1.5.5.2 Clausius Statement 16 1.5.6 Third Law of Thermodynamics 16 1.6 Thermodynamic Power Cycles 16 1.6.1 Ideal Cycle (Carnot Cycle) 17 1.6.2 Rankine Cycle 18 1.6.3 Brayton Cycle 18 1.7 Summary 21 References 21 2 Power Electronic Converters 23 2.1 Types of Power Electronic Converters 23 2.2 Power Semiconductor Devices 23 2.2.1 Thyristor 25 2.2.1.1 Line Commutation 25 2.2.1.2 Load Commutation 26 2.2.1.3 Forced Commutation 26 2.2.2 Gate Turn-OffThyristor (GTO) 26 2.2.3 Power Bipolar Junction Transistor 27 2.2.4 Power MOSFET 29 2.2.5 Insulated Gate Bipolar Transistor (IGBT) 29 2.3 ac-to-dc Converters 30 2.3.1 Single-Phase Diode Bridge Rectifiers 31 2.3.2 Three-Phase Full-Wave Bridge Diode Rectifiers 32 2.3.3 Single-Phase Fully Controlled Rectifiers 32 2.3.4 Three-Phase Fully Controlled Bridge Converter 33 2.4 dc-to-ac Converters (Inverters) 34 2.4.1 Single-Phase Voltage Source Inverters 34 2.4.2 Square-Wave PWMInverter 34 2.4.3 Single-Pulse-WidthModulation 35 2.4.4 Multiple-Pulse-WidthModulation 36 2.4.5 Sinusoidal-Pulse-WidthModulation 36 2.4.6 Three-Phase Voltage Source Inverters 37 2.4.7 Single-Phase Current Source Inverters 39 2.4.7.1 Three-Phase Current Source Inverter 39 2.5 Multilevel Inverters 40 2.5.1 Diode-Clamped Multilevel Inverter 41 2.5.2 Flying-Capacitor Multilevel Inverter 42 2.5.3 Cascaded Multicell with Different dc Source Inverter 43 2.6 Resonant Converters 43 2.6.1 Series Resonant Converter 44 2.6.1.1 Discontinuous Conduction Mode 45 2.6.2 Parallel Resonant Inverter 45 2.6.3 ZCS Resonant Converters 45 2.6.4 ZVS Resonant Converter 46 2.6.5 Resonant dc-Link Inverters 46 2.7 Matrix Converters 47 2.8 Summary 48 References 48 3 Renewable Energy Generator Technology 51 3.1 Energy Conversion 51 3.2 Power Conversion and Control ofWind Energy Systems 51 3.2.1 Induction Generator 52 3.2.2 Permanent Magnet Synchronous Generator 53 3.2.3 Linear PM Synchronous Machine 53 3.3 Operation and Control of Induction Generators forWES 53 3.3.1 Equivalent Circuit 54 3.3.2 Wound-Rotor Induction Machine 55 3.3.3 Doubly Fed Induction Generator (DFIG) 57 3.3.3.1 Equivalent Circuit of DGIG 59 3.3.3.2 Braking System 60 3.4 PermanentMagnet Synchronous Generator 60 3.4.1 Modelling of PMSG 62 3.5 Wave Energy Conversion (WEC) Technologies 63 3.5.1 Linear Permanent Magnet Synchronous Machine 64 3.5.2 Tubular Permanent Magnet LinearWave Generator (TPMLWG) 66 3.5.3 Linear Induction Machines 67 3.6 Summary 67 References 68 4 Grid-Scale Energy Storage 69 4.1 Requirement of Energy Storage 69 4.2 Types of Energy Storage Technologies 69 4.3 Electromechanical Storage 70 4.3.1 Pumped Hydro Storage (PHS) System 70 4.3.2 Underground Pumped Hydro Energy Storage 71 4.3.3 Compressed Air Energy Storage 72 4.3.4 Flywheel Storage 73 4.3.4.1 Energy Stored in Flywheel 74 4.3.4.2 Motors for Flywheels 74 4.4 Superconducting Magnetic Energy Storage 75 4.5 Supercapacitors 76 4.5.1 Equivalent Circuit 79 4.6 Chemical Storage (Batteries) 79 4.6.1 Lead–acid Battery 80 4.6.2 UltraBattery 82 4.6.3 Lithium-ion Battery 84 4.6.4 Liquid metal battery 86 4.6.5 Flow Battery 86 4.6.6 Nickle-Based Battery 87 4.7 Thermal Storage 88 4.7.1 Sensible Heat Storage 89 4.7.2 Latent Heat Storage 90 4.7.3 Thermochemical Energy Storage (TES) 91 4.8 Hydrogen Energy Storage Technology 91 4.9 Summary 92 References 93 5 Solar Energy Systems 95 5.1 Sun as Source of Energy 95 5.2 Solar Radiations on Earth 95 5.2.1 Spectral Distribution of Solar Energy 96 5.3 Measurement of Solar Radiation 97 5.3.1 Pyrheliometer 97 5.3.2 Pyranometer 99 5.3.3 Sources of Errors in RadiationMeters 100 5.3.4 Sunshine Recorder 100 5.4 Solar Radiation on Different Surfaces 101 5.4.1 Zenith and Zenith Angle 101 5.4.2 Solar Time 102 5.4.3 Latitude (∅) 102 5.4.4 Declination Angle (;;) 102 5.4.5 Hour Angle (;;) 102 5.4.6 Surface Azimuth Angle (Y) 103 5.4.7 Tilt Angle (;;) 103 5.4.8 Angle of Incidence 103 5.4.9 Solar Radiation on an Inclined Surface 104 5.5 Utilization of Solar Energy 104 5.6 Solar Thermal Systems 105 5.6.1 Flat-Plate Collectors 106 5.6.1.1 Thermal Performance of Collector 108 5.6.2 Evacuated Tube Collector 108 5.6.2.1 Direct-Flow Evacuated Tube Collector 109 5.6.2.2 Heat-Pipe Evacuated Tube Collector 109 5.6.3 Parabolic Collectors 111 5.6.4 Linear Fresnel Reflector (LFR) 112 5.6.5 Parabolic Trough Collector (PTC) 113 5.6.6 Cylindrical Trough Collector (CTC) 114 5.6.7 Parabolic Dish Reflector 115 5.6.8 Heliostat Field Collector (HFC) 116 5.7 Application of Solar Energy 117 5.7.1 SolarWater Heating 117 5.7.2 Passive Systems with Thermosiphon Circulation 117 5.7.3 Integrated Collector Storage Systems (Passive) 119 5.7.4 Active Solar Systems 119 5.7.4.1 Direct Circulation Systems 119 5.7.4.2 Indirect Circulation (Closed-Loop) Systems 120 5.7.5 Air Heating Systems 120 5.8 Solar Thermal Power Generation 122 5.9 Desalination ofWater 122 5.10 Steam Pressurization Systems Using Heat Energy 123 5.11 Summary 124 References 124 6 Photovoltaic Systems 125 6.1 PV Solar Cells and Solar Module 125 6.1.1 Semiconductor Technology 126 6.2 Solar Cell Characteristics 127 6.2.1 Equivalent Circuit 129 6.2.2 Solar PV Module 129 6.2.3 Series and Parallel Connections of Cells 129 6.2.4 Solar PV Panel 131 6.2.5 PV Array 132 6.2.5.1 Design of PV System 132 6.3 Maximizing Power Output of PV Array 133 6.3.1 Solar Tracking 134 6.3.2 Design of Simple Automatic Solar Tracker 134 6.3.3 Load Matching for Optimal Operation 135 6.4 Maximum Power Point Tracking Algorithm 135 6.4.1 Constant-VoltageMethod 136 6.4.2 Hill-Climbing/Perturb and Observe Techniques 136 6.4.2.1 Perturb and Observe 137 6.4.3 Incremental Conductance (IC) 137 6.5 Types of Solar Cells and Technologies 138 6.5.1 Crystalline Solar Cells 138 6.5.1.1 Monocrystalline Solar Cells 139 6.5.1.2 Polycrystalline Silicon Cells 140 6.6 Thin-Film Solar Cells 140 6.6.1 Amorphous Silicon Solar Cells (a-Si) 141 6.6.2 Cadmium Telluride (CdTe) 142 6.6.3 Copper Indium Gallium Diselenide (CIGS) 143 6.6.4 Copper Indium Selenide (CIS) 143 6.6.5 Crystalline Silicon (c-si)Thin-Film Solar Cells 144 6.7 Concentrating Photovoltaic Systems 144 6.8 New Emerging Technologies 144 6.9 Solar PV Systems 146 6.9.1 Grid-Connected PV System 147 6.9.2 Grid-Connected System without Battery Storage 147 6.9.3 Grid-Connected System with Battery Storage 148 6.10 Design and Control of Stand-Alone PV System 148 6.10.1 Battery Rating 149 6.11 Summary 150 References 150 7 Wind Energy 153 7.1 Wind as Source of Energy 153 7.1.1 Origin ofWind 153 7.1.2 Wind Power Potential 154 7.2 Power and Energy inWind 155 7.3 Aerodynamics ofWind Turbines 156 7.3.1 Momentum 157 7.4 Types ofWind Turbines 160 7.4.1 Horizontal-AxisWind Turbines 160 7.4.1.1 Horizontal-AxisWind Turbines withWake Rotation 161 7.4.2 Vertical-AxisWind Turbines 164 7.4.3 Main Components ofWind Turbine 166 7.4.3.1 Drive Train 167 7.5 Dynamics and Control ofWind Turbines 167 7.5.1 Pitch Control 168 7.5.2 Yaw Control 169 7.5.3 Passive and Active Stall Power Control 169 7.5.3.1 Passive Stall Control 169 7.5.3.2 Active Stall Control 169 7.6 Wind Turbine ConditionMonitoring 170 7.7 Wind Energy Conversion Systems (WECS) 171 7.7.1 Based on Capacity of Power Generation 171 7.7.2 Systems without Power Electronics 171 7.8 OffshoreWind Energy 174 7.8.1 OffshoreWind Turbines 174 7.8.2 Foundation 174 7.8.3 Electrical Connection and Installation 174 7.8.4 Operation and Maintenance 175 7.9 Advantages of OffshoreWind Energy Systems 175 7.10 Environmental Impact ofWind Energy Systems 175 7.10.1 Impact of Noise 175 7.10.2 Electromagnetic Interference 176 7.11 Combining theWind Power Generation System with Energy Storage 176 7.12 Summary 176 References 176 8 Biomass Energy Systems 179 8.1 Biomass Energy 179 8.2 Biomass Production 181 8.2.1 Forest Industries 182 8.2.2 Forest Residues 182 8.2.2.1 ForestThinnings 183 8.2.3 Agriculture Residues 183 8.2.4 Energy Crops 183 8.2.5 Food and IndustrialWastes 184 8.3 Biomass Conversion Process 185 8.4 Thermochemical Conversion 185 8.4.1 Combustion 185 8.4.2 Gasification 186 8.4.2.1 Applications 190 8.4.3 Pyrolysis 190 8.4.3.1 Torrefaction 193 8.4.4 Liquefaction 194 8.5 Biochemical/Biological Conversion 194 8.5.1 Fermentation 195 8.5.2 Anaerobic Digestion 196 8.5.3 Anaerobic Digestion Technologies Suitable for Dairy Manure 198 8.6 Classification of Biogas Plants 199 8.7 Mechanical Extraction (with Esterification) 200 8.8 Municipal SolidWaste to Energy Conversion 201 8.9 The Production of Electricity fromWood and Other Solid Biomass 203 8.10 Summary 205 References 205 9 Geothermal Energy 207 9.1 The Origin of Geothermal Energy 207 9.2 Types of Geothermal Resources 208 9.3 Hydrothermal Resources 210 9.3.1 Vapour-Dominated Systems 211 9.3.2 Water-Dominated Systems 212 9.4 The Geopressured Resources 213 9.5 Hard Rock Resources 214 9.5.1 Solidified (Hot Dry Rock Resources) 214 9.5.2 Part Still Molten (Magma) 214 9.6 Energy Contents of Geothermal Resources 215 9.6.1 Hard Dry Rock Resources 215 9.7 Exploration of Geothermal Resources 216 9.8 Geophysical Methods in Geothermal Exploration 217 9.8.1 Thermal Methods 217 9.8.2 Electrical Methods 217 9.8.3 MagneticMeasurements 218 9.9 Geochemical Techniques 219 9.9.1 Water or Solute Geothermometers 219 9.9.1.1 Na-K Geothermometer 219 9.9.1.2 Na-K-Ca Geothermometer 220 9.9.2 Gas Thermometers 220 9.9.3 Isotopes 220 9.9.4 Drilling 220 9.10 Utilization of Geothermal Resource 221 9.10.1 Electricity Generation from Geothermal Resources 222 9.10.2 Dry Steam Power Plants 222 9.10.3 Single-Flash Steam Power Plant 223 9.10.4 Double-Flash Power Plant 225 9.10.5 Binary Cycle Power Plant 226 9.11 Enhanced Geothermal Systems 227 9.11.1 Combined or Hybrid Plants 227 9.11.2 Combined Heat and Power (CHP) Plants 227 9.12 Direct Use of Geothermal Energy 228 9.13 Environmental Impact 230 9.14 Summary 231 References 231 10 Ocean Energy 233 10.1 Energy from Ocean 233 10.2 Harnessing the Tidal Energy 235 10.2.1 Tidal Barrage Power 236 10.2.2 Tidal Barrage Technologies 236 10.2.3 Tidal Stream Power 237 10.2.4 Dynamic Tidal Power Generation 238 10.3 Energy of Tides 238 10.4 Turbine Technologies 240 10.4.1 Horizontal-Axis Turbines 240 10.4.2 Vertical-Axis Turbines 241 10.4.3 Reciprocating Hydrofoils 242 10.5 Support Structure 242 10.5.1 Gravity Structures 242 10.5.2 Piled Structures 242 10.5.3 Floating Foundations 243 10.6 Wave Energy 243 10.6.1 Wave Energy and Power 243 10.7 Wave Energy Converters 245 10.7.1 OscillatingWater Column 245 10.7.2 Oscillating Body 246 10.7.3 Overtopping Converters (or Terminators) 246 10.7.4 Point Absorbers and Attenuators 247 10.8 Power Takeoff Systems 248 10.8.1 Air Turbines for OWC 249 10.8.2 Hydraulic Systems 249 10.8.3 Water Turbines 250 10.8.4 Direct Drive 250 10.9 Piezoelectric Generators 252 10.9.1 Power Extraction Systems 253 10.10 OceanThermal Energy Conversion 254 10.10.1 Technology for OTEC 254 10.10.1.1 Closed-Cycle 255 10.10.1.2 Open-Cycle 256 10.10.1.3 Hybrid Systems 257 10.11 Summary 258 References 258 11 Fuel Cells 261 11.1 Fuel Cell Technologies 261 11.2 Types of Fuel Cells 262 11.3 Proton Exchange Membrane (PEM) Fuel Cell 262 11.3.1 Water Management 263 11.3.2 Fuel Requirement 265 11.3.3 Reforming Technologies 265 11.3.3.1 Partial Oxidation 266 11.3.4 Hydrogen Storage 266 11.3.5 Catalysts for PEM Fuel Cell 267 11.4 Solid Oxide Fuel Cell 267 11.4.1 Electrolytes for SOFC 268 11.5 Molten Carbonate Fuel Cell 269 11.6 Phosphoric Acid Fuel Cell 270 11.7 Alkaline Fuel Cell 272 11.8 Direct Methanol Fuel Cell 274 11.8.1 CO Removal 276 11.9 Fuel Cell Stacks 276 11.9.1 Cooling with Separate Airflow 277 11.9.2 Liquid Cooling 277 11.10 Fuel Cell Applications 278 11.10.1 Application in Automobile Industry 278 11.10.2 Stationary Power Applications 278 11.10.3 Portable Applications 279 11.11 Modelling of Fuel Cell 280 11.11.1 Steady-StateModel 280 11.12 Summary 281 References 281 12 Small Hydropower Plant 283 12.1 Hydropower 283 12.2 Classification of Hydropower Plants 284 12.2.1 Basics of Hydropower Generation 285 12.3 Resource Assessment 285 12.3.1 Velocity Area Method 286 12.3.2 Float Method 287 12.4 System Components 288 12.4.1 DiversionWeir 288 12.4.1.1 Side Intake withoutWeir 288 12.4.1.2 Side Intake withWeir 288 12.4.1.3 Bottom Intake 288 12.4.2 Water Conductor System or Channels 289 12.4.3 Forebay Tank 289 12.4.4 Penstock 289 12.4.5 Spillways 289 12.5 Turbines 290 12.6 Impulse Turbines 290 12.6.1 Pelton Turbine 291 12.6.2 Cross-Flow Turbine 292 12.6.3 Turgo Turbine 293 12.7 Reaction Turbine 294 12.7.1 The Propeller Turbine 295 12.7.2 Reverse Pump Turbines 295 12.8 Generators for Small Hydro Plants 296 12.9 Design Considerations of Micro-Hydropower Plants 297 12.9.1 Example 299 References 299 13 Control of Grid-Connected Photovoltaic and Wind Energy Systems 301 13.1 Introduction 301 13.2 Operation and Control of Grid-Connected PV System 302 13.2.1 Control of Single-Phase PV System 302 13.2.1.1 Control of PV-Side dc/dc Converter 303 13.2.1.2 Control of Grid-Side Inverter 304 13.2.1.3 Inner Current Loop 305 13.3 Grid Synchronization 305 13.4 Control of Three-Phase Grid-Connected PV system 306 13.5 Selection of Inverter for PV System 307 13.5.1 Central Inverters 307 13.5.2 String Inverter 308 13.5.3 ac Module Inverter 309 13.5.4 Multi-String Inverters 310 13.6 Power Decoupling 311 13.7 Isolation Between Input and Output 311 13.8 Transformers and Interconnections 311 13.8.1 Transformerless PV Inverter Topologies 312 13.9 Filters for Grid-Connected PV Inverters 314 13.10 Islanding DetectionMethods 314 13.11 Operation and Control of Grid-ConnectedWind Energy System 315 13.11.1 Grid Integration ofWind Turbine System 316 13.11.2 Power Electronics inWind Energy System 317 13.11.3 Control of Doubly Fed Induction Generator–BasedWind Turbine Systems 318 13.11.3.1 Control of a DFIG under Unbalanced Grid 319 13.11.4 PMSG-BasedWind Energy Conversion System 320 13.11.4.1 Current-Source-Based PMSG 321 13.12 Summary 322 References 322 14 Renewable Energy Sources Integration in Microgrid 325 14.1 Microgrid 325 14.2 Types of Microgrids 327 14.3 dc Microgrid 327 14.3.1 Control Methods for dc Grid System 329 14.3.2 Energy Storage System 330 14.3.3 Operational Modes of dc Microgrid 330 14.3.3.1 Mode 1: IslandingMode (Battery Discharge) 330 14.3.3.2 Mode 2: IslandingMode (Excess Power Available) 331 14.3.3.3 Mode 3: Grid-Connected Mode (Power Taken from Grid) 331 14.3.3.4 Mode 4: Grid-Connected Mode (Power Supplied to Grid) 332 14.3.4 Application of dc Microgrids 332 14.4 ac Microgrid 332 14.4.1 Interconnected or Grid-Connected Mode 333 14.4.2 Islanded Mode 334 14.5 Control of ac Microgrid in Grid-Connected Mode 334 14.5.1 Primary Control 337 14.5.2 Secondary Control 337 14.5.3 Tertiary Control 338 14.6 Autonomous Operation of Microgrid 338 14.6.1 Islanding Detection 339 14.6.1.1 ImpedanceMeasurement Method 340 14.6.1.2 Slip-Mode Frequency Shift (SMS) Method 340 14.6.1.3 Active Frequency Drift Method 340 14.6.1.4 Sandia Frequency Shift (SFS) 341 14.6.2 Stability Issues 342 14.7 Load Frequency Control in Microgrid 342 14.7.1 Secondary Load-Frequency Control 343 14.8 Combined ac/dc Microgrid 343 14.8.1 Operation and Control of Hybrid ac/dc Grid 344 14.8.2 Modelling 345 14.9 Summary 345 References 345 Index 347

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Book SynopsisOffers a comprehensive introduction to the issues of control of power systems during cascading outages and restoration process Power System Control Under Cascading Failures offers comprehensive coverage of three major topics related to prevention of cascading power outages in a power transmission grid: modelling and analysis, system separation and power system restoration. The book examines modelling and analysis of cascading failures for reliable and efficient simulation and better understanding of important mechanisms, root causes and propagation patterns of failures and power outages. Second, it covers controlled system separation to mitigate cascading failures addressing key questions such as where, when and how to separate. Third, the text explores optimal system restoration from cascading power outages and blackouts by well-designed milestones, optimised procedures and emerging techniques. The authors noted experts in the field include state-of-thTable of ContentsAbout the Companion Website xiii 1 Introduction 1 1.1 Importance of Modeling and Understanding Cascading Failures 1 1.1.1 Cascading Failures 1 1.1.2 Challenges in Modeling and Understanding Cascading Failures 4 1.2 Importance of Controlled System Separation 6 1.2.1 Mitigation of Cascading Failures 6 1.2.2 Uncontrolled and Controlled System Separations 7 1.3 Constructing Restoration Strategies 9 1.3.1 Importance of System Restoration 9 1.3.2 Classification of System Restoration Strategies 10 1.3.3 Challenges of System Restoration 13 1.4 Overview of the Book 15 References 18 2 Modeling of Cascading Failures 23 2.1 General Cascading Failure Models 23 2.1.1 Bak–Tang–Wiesenfeld Sandpile Model 23 2.1.2 Failure‐Tolerance Sandpile Model 24 2.1.3 Motter–Lai Model 30 2.1.4 Influence Model 30 2.1.5 Binary‐Decision Model 33 2.1.6 Coupled Map Lattice Model 34 2.1.7 CASCADE Model 35 2.1.8 Interdependent Failure Model 37 2.2 Power System Cascading Failure Models 39 2.2.1 Hidden Failure Model 39 2.2.2 Manchester Model 40 2.2.3 OPA Model 42 2.2.4 Improved OPA Model 46 2.2.5 OPA Model with Slow Process 49 2.2.6 AC OPA Model 58 2.2.7 Cascading Failure Models Considering Dynamics and Detailed Protections 62 References 64 3 Understanding Cascading Failures 69 3.1 Self‐ Organized Criticality 70 3.1.1 SOC Theory 70 3.1.2 Evidence of SOC in Blackout Data 71 3.2 Branching Processes 72 3.2.1 Definition of the Galton–Watson Branching Process 74 3.2.2 Estimation of Mean of the Offspring Distribution 74 3.2.3 Estimation of Variance of the Offspring Distribution 75 3.2.4 Processing and Discretization of Continuous Data 78 3.2.5 Estimation of Distribution of Total Outages 81 3.2.6 Statistical Insight of Branching Process Parameters 81 3.2.7 Branching Processes Applied to Line Outage Data 82 3.2.8 Branching Processes Applied to Load Shed Data 84 3.2.9 Cross‐Validation for Branching Processes 85 3.2.10 Efficiency Improvement by Branching Processes 85 3.3 Multitype Branching Processes 87 3.3.1 Estimation of Multitype Branching Process Parameters 88 3.3.2 Estimation of Joint Probability Distribution of Total Outages 90 3.3.3 An Example for a Two‐Type Branching Process 91 3.3.4 Validation of Estimated Joint Distribution 92 3.3.5 Number of Cascades Needed for Multitype Branching Processes 94 3.3.6 Estimated Parameters of Branching Processes 96 3.3.7 Estimated Joint Distribution of Total Outages 98 3.3.8 Cross‐Validation for Multitype Branching Processes 100 3.3.9 Predicting Joint Distribution from One Type of Outage 102 3.3.10 Estimating Failure Propagation of Three Types of Outages 104 3.4 Failure Interaction Analysis 105 3.4.1 Estimation of Interactions between Component Failures 106 3.4.2 Identification of Key Links and Key Components 108 3.4.3 Interaction Model 111 3.4.4 Validation of Interaction Model 113 3.4.5 Number of Cascades Needed for Failure Interaction Analysis 115 3.4.6 Estimated Interaction Matrix and Interaction Network 119 3.4.7 Identified Key Links and Key Components 121 3.4.8 Interaction Model Validation 125 3.4.9 Cascading Failure Mitigation 129 3.4.10 Efficiency Improvement by Interaction Model 134 References 137 4 Strategies for Controlled System Separation 141 4.1 Questions to Answer 141 4.2 Literature Review 142 4.3 Constraints on Separation Points 144 4.4 Graph Models of a Power Network 148 4.4.1 Undirected Node‐Weighted Graph 149 4.4.2 Directed Edge‐Weighted Graph 152 4.5 Generator Grouping 153 4.5.1 Slow Coherency Analysis 154 4.5.2 Elementary Coherent Groups 158 4.6 Finding Separation Points 160 4.6.1 Formulations of the Problem 160 4.6.2 Computational Complexity 164 4.6.3 Network Reduction 167 4.6.4 Network Decomposition for Parallel Processing 173 4.6.5 Application of the Ordered Binary Decision Diagram 175 4.6.6 Checking the Transmission Capacity and Small Disruption Constraints 185 4.6.7 Checking All Constraints in Three Steps 190 References 192 5 Online Decision Support for Controlled System Separation 197 5.1 Online Decision on the Separation Strategy 197 5.1.1 Spectral Analysis-Based Method 198 5.1.2 Frequency‐Amplitude Characteristics of Electromechanical Oscillation 199 5.1.3 Phase‐Locked Loop-Based Method 204 5.1.4 Timing of Controlled Separation 210 5.2 WAMS‐ Based Unified Framework for Controlled System Separation 212 5.2.1 WAMS‐Based Three‐Stage CSS Scheme 212 5.2.2 Offline Analysis Stage 214 5.2.3 Online Monitoring Stage 216 5.2.4 Real‐Time Control Stage 221 References 223 6 Constraints of System Restoration 225 6.1 Physical Constraints During Restoration 225 6.1.1 Generating Unit Start‐Up 225 6.1.2 System Sectionalizing and Reconfiguration 230 6.1.3 Load Restoration 233 6.2 Electromagnetic Transients During System Restoration 235 6.2.1 Generator Self‐Excitation 237 6.2.2 Switching Overvoltage 237 6.2.3 Resonant Overvoltage in the Case of Energizing No‐Load Transformer 242 6.2.4 Impact of Magnetizing Inrush Current on Transformer 245 6.2.5 Voltage and Frequency Analysis in Picking up Load 247 References 251 7 Restoration Methodology and Implementation Algorithms 255 7.1 Algorithms for Generating Unit Start‐Up 255 7.1.1 A General Bilevel Framework 255 7.1.2 Algorithms for the Primary Problem 260 7.1.3 Algorithms for the Second Problem 265 7.2 Algorithms for Load Restoration 269 7.2.1 Estimate Operational Region Bound 271 7.2.2 Formulate MINLR Model to Maximize Load Pickup 272 7.2.3 Branch‐and‐Cut Solver: Design and Justification 275 7.2.4 Selection of Branching Methods 278 7.3 Case Studies 278 7.3.1 Illustrative Example for Restoring Generating Units 278 7.3.2 Optimal Load Restoration Strategies for RTS 24‐Bus System 283 7.3.3 Optimal Load Restoration Strategies for IEEE 118‐Bus System 287 References 291 8 Renewable and Energy Storage in System Restoration 295 8.1 Planning of Renewable Generators in System Restoration 295 8.1.1 Renewables for System Restoration 295 8.1.2 The Offline Restoration Tool Using Renewable Energy Resources 296 8.1.3 System Restoration with Renewables’ Participation 298 8.2 Operation and Control of Renewable Generators in System Restoration 305 8.2.1 Prerequisites of Type 3 WTs for System Restoration 307 8.2.2 Problem Setup of Type 3 WTs for System Restoration 308 8.2.3 Black‐Starting Control and Sequence of Type 3 WTs 314 8.2.4 Autonomous Frequency Mechanism of a Type 3 WT-Based Stand‐Alone System 317 8.2.5 Simulation Study 320 8.3 Energy Storage in System Restoration 323 8.3.1 Pumped‐Storage Hydro Units in Restoration 323 8.3.2 Batteries for System Restoration 332 8.3.3 Electric Vehicles in System Restoration 340 References 351 9 Emerging Technologies in System Restoration 357 9.1 Applications of FACTS and HVDC 357 9.1.1 LCC‐HVDC Technology for System Restoration 357 9.1.2 VSC‐HVDC Technology for System Restoration 363 9.1.3 FACTS Technology for System Restoration 370 9.2 Applications of PMUs 376 9.2.1 Review of PMU 376 9.2.2 System Restoration with PMU Measurements 378 9.3 Microgrid in System Restoration 385 9.3.1 Microgrid‐Based Restoration 385 9.3.2 Demonstration and Practice 388 References 393 10 Black-Start Capability Assessment and Optimization 399 10.1 Background of Black Start 399 10.1.1 Definition of Black Start 399 10.1.2 Constraints During BS 400 10.1.3 BS Service Procurement 401 10.1.4 Power System Restoration Procedure 403 10.2 BS Capability Assessment 404 10.2.1 Installation Criteria of New BS Generators 404 10.2.2 Optimal Installation Strategy of BS Capability 407 10.2.3 Examples 408 10.3 Optimal BS Capability 411 10.3.1 Problem Formulation 411 10.3.2 Solution Algorithm 418 10.3.3 Examples 421 References 431 Index 433

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Book SynopsisTHE PERFECT GUIDE TO FLAT PANEL DISPLAYS FOR RESEARCHERS AND INDUSTRY PERSONNEL ALIKE Introduction to Flat Panel Displays, 2nd Edition is the leading introductory reference to state-of-the-art flat panel display technologies. The 2nd edition has been newly updated to include the latest developments for high pixel resolution support, high brightness, improved contrast settings, and low power consumption. The 2nd edition has also been updated to include the latest developments of head-mounted displays for virtual and augmented reality applications. Introduction to Flat Panel Displays introduces and updates both the fundamental physics and materials concepts underlying flat panel display technology and their application to smart phones, ultra-high definitions TVs, computers, and virtual and augmented reality systems. The book includes new information on quantum-dot enhanced LCDs, device configurations and performance, and nTable of ContentsSeries Editor’s Foreword xiii 1 Flat Panel Displays 1 1.1 Introduction 1 1.2 Emissive and non-emissive Displays 4 1.3 Display Specifications 4 1.3.1 Physical Parameters 5 1.3.2 Brightness and Color 7 1.3.3 Contrast Ratio 8 1.3.4 Spatial and Temporal Characteristics 8 1.3.5 Efficiency and Power Consumption 9 1.3.6 Flexible Displays 9 1.4 Applications of Flat Panel Displays 9 1.4.1 Liquid Crystal Displays 10 1.4.2 Light-Emitting Diodes 10 1.4.3 Organic Light-Emitting Devices 11 1.4.4 Reflective Displays 11 1.4.5 Head-Mounted Displays 12 1.4.6 Touch Panel Technologies 12 References 13 2 Color Science and Engineering 15 2.1 Introduction 15 2.2 Photometry 16 2.3 The Eye 18 2.4 Colorimetry 22 2.4.1 Trichromatic Space 22 2.4.2 CIE 1931 Colormetric Observer 24 2.4.3 CIE 1976 Uniform Color System 27 2.4.4 CIECAM 02 Color Appearance Model 30 2.4.5 Color Gamut 31 2.4.6 Light Sources 32 2.4.6.1 Sunlight and Blackbody Radiators 32 2.4.6.2 Light Sources for Transmissive, Reflective, and Projection Displays 33 2.4.6.3 Color Rendering Index 34 2.5 Production and Reproduction of Colors 34 2.6 Display Measurements 35 Homework Problems 36 References 36 3 Thin Film Transistors 39 3.1 Introduction 39 3.2 Basic Concepts of Crystalline Semiconductor Materials 39 3.2.1 Band Structure of Crystalline Semiconductors 40 3.2.2 Intrinsic and Extrinsic Semiconductors 43 3.3 Classification of Silicon Materials 46 3.4 Hydrogenated Amorphous Silicon (a-Si:H) 46 3.4.1 Electronic Structure of a:Si-H 47 3.4.2 Carrier Transport in a-Si:H 48 3.4.3 Fabrication of a-Si:H 48 3.5 Polycrystalline Silicon 49 3.5.1 Carrier Transport in Polycrystalline Silicon 49 3.5.2 Fabrication of Polycrystalline-Silicon 50 3.6 Thin-Film Transistors 52 3.6.1 Fundamentals of TFTs 52 3.6.2 a-Si:H TFTs 55 3.6.3 Poly-Si TFTs 55 3.6.4 Organic TFTs 56 3.6.5 Oxide Semiconductor TFTs 57 3.6.6 Flexible TFT Technology 59 3.7 PM and AM Driving Schemes 61 Homework Problems 67 References 67 4 Liquid Crystal Displays 71 4.1 Introduction 71 4.2 Transmissive LCDs 72 4.3 Liquid Crystal Materials 74 4.3.1 Phase Transition Temperatures 75 4.3.2 Eutectic Mixtures 75 4.3.3 Dielectric Constants 77 4.3.4 Elastic Constants 78 4.3.5 Rotational Viscosity 79 4.3.6 Optical Properties 80 4.3.7 Refractive Indices 80 4.3.7.1 Wavelength Effect 80 4.3.7.2 Temperature Effect 82 4.4 Liquid Crystal Alignment 83 4.5 Homogeneous Cell 84 4.5.1 Phase Retardation Effect 85 4.5.2 Voltage Dependent Transmittance 86 4.6 Twisted Nematic (TN) 87 4.6.1 Optical Transmittance 87 4.6.2 Viewing Angle 89 4.6.3 Film-Compensated TN 90 4.7 In-Plane Switching (IPS) 91 4.7.1 Device Structure 92 4.7.2 Voltage-Dependent Transmittance 92 4.7.3 Viewing Angle 92 4.7.4 Phase Compensation Films 93 4.8 Fringe Field Switching (FFS) 95 4.8.1 Device Configurations 95 4.8.2 n-FFS versus p-FFS 96 4.9 Vertical Alignment (VA) 98 4.9.1 Voltage-Dependent Transmittance 98 4.9.2 Response Time 99 4.9.3 Overdrive and Undershoot Addressing 101 4.9.4 Multi-domain Vertical Alignment (MVA) 102 4.10 Ambient Contrast Ratio 103 4.10.1 Modeling of Ambient Contrast Ratio 103 4.10.2 Ambient Contrast Ratio of LCD 103 4.10.3 Ambient Contrast Ratio of OLED 104 4.10.4 Simulated ACR for Mobile Displays 105 4.10.5 Simulated ACR for TVs 105 4.10.6 Simulated Ambient Isocontrast Contour 106 4.10.6.1 Mobile Displays 106 4.10.6.2 Large-Sized TVs 108 4.10.7 Improving LCD’s ACR 109 4.10.8 Improving OLED’s ACR 110 4.11 Motion Picture Response Time (MPRT) 112 4.12 Wide Color Gamut 114 4.12.1 Material Synthesis and Characterizations 115 4.12.2 Device Configurations 116 4.13 High Dynamic Range 118 4.13.1 Mini-LED Backlit LCDs 118 4.13.2 Dual-Panel LCDs 120 4.14 Future Directions 121 Homework Problems 123 References 124 5 Light-Emitting Diodes 135 5.1 Introduction 135 5.2 Material Systems 138 5.2.1 AlGaAs and AlGaInP Material Systems for Red and Yellow LEDs 140 5.2.2 GaN-Based Systems for Green, Blue, UV and UV LEDs 141 5.2.3 White LEDs 143 5.3 Diode Characteristics 146 5.3.1 p- and n-Layer 147 5.3.2 Depletion Region 148 5.3.3 J–V Characteristics 150 5.3.4 Heterojunction Structures 152 5.3.5 Quantum-Well, -Wire, and -Dot Structures 152 5.4 Light-Emitting Characteristics 154 5.4.1 Recombination Model 154 5.4.2 L-J Characteristics 155 5.4.3 Spectral Characteristics 156 5.4.4 Efficiency Droop 159 5.5 Device Fabrication 160 5.5.1 Epitaxy 161 5.5.2 Process Flow and Device Structure Design 165 5.5.3 Extraction Efficiency Improvement 166 5.5.4 Packaging 168 5.6 Applications 169 5.6.1 Traffic Signals, Electronic Signage and Huge Displays 169 5.6.2 LCD Backlight 170 5.6.3 General Lighting 172 5.6.4 Micro-LEDs 173 Homework Problems 175 References 175 6 Organic Light-Emitting Devices 179 6.1 Introduction 179 6.2 Energy States in Organic Materials 180 6.3 Photophysical Processes 182 6.3.1 Franck–Condon Principle 182 6.3.2 Fluorescence and Phosphorescence 183 6.3.3 Jablonski Diagram 185 6.3.4 Intermolecular Processes 186 6.3.4.1 Energy Transfer Processes 186 6.3.4.2 Excimer and Exciplex Formation 188 6.3.4.3 Quenching Processes 188 6.3.5 Quantum Yield Calculation 189 6.4 Carrier Injection, Transport, and Recombination 191 6.4.1 Richardson–Schottky Thermionic Emission 192 6.4.2 SCLC, TCLC, and P–F Mobility 193 6.4.3 Charge Recombination 195 6.4.4 Electromagnetic Wave Radiation 195 6.5 Structure, Fabrication and Characterization 197 6.5.1 Device Structure of Organic Light-Emitting Device 198 6.5.1.1 Two-Layer Organic Light-Emitting Device 198 6.5.1.2 Matrix Doping in the EML 200 6.5.1.3 HIL, EIL, and p-i-n Structure 202 6.5.1.4 Top-Emission and Transparent OLEDs 204 6.5.2 Polymer OLED 205 6.5.3 Device Fabrication 206 6.5.3.1 Thin-film Formation 207 6.5.3.2 Encapsulation and Passivation 210 6.5.3.3 Device Structures for AM Driving 211 6.5.4 Electrical and Optical Characteristics 212 6.5.5 Degradation Mechanisms 214 6.6 Triplet Exciton Utilization 219 6.6.1 Phosphorescent OLEDs 219 6.6.2 Triplet-Triplet Annihilation OLED 221 6.6.3 Thermally Activated Delayed Fluorescence 222 6.6.4 Exciplex-Based OLED 223 6.7 Tandem Structure 224 6.8 Improvement of Extraction Efficiency 226 6.9 White OLEDs 229 6.10 Quantum-Dot Light-Emitting Diode 231 6.11 Applications 233 6.11.1 Mobile OLED Display 233 6.11.2 OLED TV 234 6.11.3 OLED Lighting 235 6.11.4 Flexible OLEDs 235 6.11.5 Novel Displays 236 Homework Problems 236 References 237 7 Reflective Displays 245 7.1 Introduction 245 7.2 Electrophoretic Displays 245 7.3 Reflective Liquid Crystal Displays 249 7.4 Reflective Display Based on Optical Interference (Mirasol Display) 253 7.5 Electrowetting Display 254 7.6 Comparison of Different Reflective Display Technologies 256 Homework Problems 256 References 257 8 Fundamentals of Head-Mounted Displays for Virtual and Augmented Reality 259 8.1 Introduction 259 8.2 Human Visual System 262 8.3 Fundamentals of Head-mounted Displays 265 8.3.1 Paraxial Optical Specifications 265 8.3.2 Microdisplay Sources 272 8.3.3 HMD Optics Principles and Architectures 275 8.3.4 Optical Combiner 280 8.4 HMD Optical Designs and Performance Specifications 286 8.4.1 HMD Optical Designs 286 8.4.2 HMD Optical Performance Specifications 290 8.5 Advanced HMD Technologies 298 8.5.1 Eyetracked and Fovea-Contingent HMDs 299 8.5.2 Dynamic Range Enhancement 302 8.5.3 Addressable Focus Cues in HMDs 305 8.5.3.1 Extended Depth of Field Displays 307 8.5.3.2 Vari-Focal Plane (VFP) Displays 308 8.5.3.3 Multi-Focal Plane (MFP) Displays 309 8.5.3.4 Head-Mounted Light Field (LF) Displays 315 8.5.4 Head-Mounted Light Field Displays 316 8.5.4.1 InI-Based Head-Mounted Light Field Displays 317 8.5.4.2 Computational Multi-Layer Head-Mounted Light Field Displays 321 8.5.5 Mutual Occlusion Capability 323 References 328 9 Touch Panel Technology 337 9.1 Introduction 337 9.2 Resistive Touch Panel 338 9.3 Capacitive Touch Panel 339 9.4 On-Cell and In-Cell Touch Panel 344 9.5 Optical Sensing for Large Panels 347 Homework Problems 348 References 348 Index 351

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Book SynopsisThis book provides an overall view of the new and highly promising materials and thin film deposition techniques for printable solar cell applications. The book is organized in four parts. Organic and inorganic hybrid materials and solar cell manufacturing techniques are covered in Part I.Table of ContentsPreface xv Part I Hybrid Materials and Process Technologies for Printable Solar Cells 1 Organic and Inorganic Hybrid Solar Cells 3 Serap Güneş and Niyazi Serdar Sariciftci 1.1 Introduction 4 1.2 Organic/Inorganic Hybrid Solar Cells 5 1.2.1 Introduction to Hybrid Solar Cells 5 1.2.2 Hybrid Solar Cells 5 1.2.2.1 Operational Principles of Bulk Heterojunction Hybrid Solar Cells 5 1.2.2.2 Bulk Heterojunction Hybrid Solar Cells 8 1.2.2.3 Bilayer Heterojunction Hybrid Solar Cells 12 1.2.2.4 Inverted-Type Hybrid Bulk Heterojunction Solar Cells 15 1.2.2.5 Dye-Sensitized Solar Cells 16 1.2.2.6 Perovskite Solar Cells 21 1.3 Conclusion 23 References 25 2 Solution Processing and Thin Film Formation of Hybrid Semiconductors for Energy Applications 37 J. Ciro, J.F. Montoya, R. Betancur and F. Jaramillo 2.1 Physical Chemical Principles of Film Formation by Solution Processes: From Suspensions of Nanoparticles and Solutions to Nucleation, Growth, Coarsening and Microstructural Evolution of Films 38 2.2 Solution-Processing Techniques for Thin Film Deposition 40 2.2.1 Spin Coating 42 2.2.2 Doctor Blade 43 2.2.3 Slot-Die Coating 44 2.2.4 Spray Coating 46 2.3 Properties and Characterization of Thin Films: Transport, Active and Electrode Layers in Thin Film Solar Cells 46 2.4 Understanding the Crystallization Processes in Hybrid Semiconductor Films: Hybrid Perovskite as a Model 50 2.4.1 Thermal Transitions Revealed by DSC 50 2.4.2 Heat Transfer Processes in a Meso-Superstructured Perovskite Solar Cell 53 2.4.3 Effect of the Annealing Process on Morphology and Crystalline Properties of Perovskite Films 55 2.4.4 Role of Precursor Composition in the Crystallinity of Perovskite Films: Understanding the Role of Additives and Moisture in the Final Properties of Perovskite Layers 56 References 57 3 Organic-Inorganic Hybrid Solar Cells Based on Quantum Dots 65 Wenjin Yue 3.1 Introduction 65 3.2 Polymer/QD Solar Cells 67 3.2.1 Working Principle 67 3.2.2 Device Parameters 68 3.2.2.1 Open-Circuit Voltage (Voc) 68 3.2.2.2 Short-Circuit Current (Jsc) 68 3.2.2.3 Fill Factor (FF) 69 3.2.3 Device Structure 70 3.2.4 Progress of Polymer/QD Solar Cells 71 3.2.4.1 Device Based on Cd Compound 71 3.2.4.2 Device Based on Pb Compound 74 3.2.4.3 Device Based on CuInS2 76 3.2.5 Strategy for Improved Device Performance 78 3.2.5.1 QDs Surface Treatment 78 3.2.5.2 In-Situ Synthesis of QDs 81 3.2.5.3 Polymer End-Group Functionalization 82 3.3 Outlooks and Conclusions 83 Acknowledgment 83 4 Hole Transporting Layers in Printable Solar Cells 93 David Curiel and Miriam Más-Montoya 4.1 Introduction 94 4.2 Hole Transporting Layers in Organic Solar Cells 97 4.2.1 Utility of Hole Transporting Layers 97 4.2.1.1 Energy Level Alignment at the Interfaces and Effect on the Open-Circuit Voltage 98 4.1.1.2 Definition of Device Polarity, Charge Transport and Use as Blocking Layer 102 4.1.1.3 Optical Spacer 103 4.1.1.4 Modulation of the Active Layer Morphology and Use as Protective Layer 103 4.1.2 Overview of Materials Used as Hole Transporting Layers 104 4.1.2.1 Polymers 104 4.1.2.2 Small Molecules 109 4.1.2.3 Metals 112 4.1.2.4 Metal Oxides 112 4.1.2.5 Metal Salts 116 4.1.2.6 Carbon Nanotubes 116 4.1.2.7 Graphene-Based Materials 116 4.1.2.8 Self-Assembled Monolayers 119 4.2 Hole Transporting Layers in Dye-Sensitized Solar Cells 121 4.2.1 Overview of Materials Used as Hole Transporting Layers 123 4.2.1.1 Small Molecules 123 4.2.1.2 Polymers 126 4.3 Hole Transporting Layers in Perovskite Solar Cells 127 4.3.1 Overview of Materials Used as Hole Transporting Layers 128 4.3.1.1 Small Molecules 128 4.3.1.2 Polymers 137 4.3.1.3 Metal Oxides 139 4.3.1.4 Metal Salts 140 4.3.1.5 Carbon Nanotubes 141 4.3.1.6 Graphene-Based Materials 142 4.4 Concluding Remarks 143 5 Printable Solar Cells 163 Alexander Kovalenko and Michal Hrabal 5.1 Introduction 164 5.2 Printable Solar Cells Working Principles 165 5.2.1 CIGS Solar Cells 165 5.2.2 Perovskite Solar Cells 167 5.2.3 Organic Solar Cells 170 5.2.4 Printable Charge-Carrier Selective Layers 172 5.3 Solution-Based Deposition of Thin Film Layers 173 5.3.1 Coating Techniques 174 5.3.1.1 Casting 174 5.3.1.2 Spin Coating 174 5.3.1.3 Blade Coating 176 5.3.1.4 Slot-Die Coating 177 5.3.2 Printing Techniques 179 5.3.2.1 Screen Printing 180 5.3.2.2 Gravure Printing 182 5.3.2.3 Flexographic Printing 184 5.3.2.4 Inkjet Printing 185 5.4 Characterization Techniques 189 5.4.1 Characterization of Thin Layers 189 5.4.2 Electrical Characterization of Solar Cells 190 5.5 Conclusion 194 References 197 Part II Organic Materials and Process Technologies for Printable Solar Cells 6 Spray-Coated Organic Solar Cells 205 Yifan Zheng and Junsheng Yu 6.1 Introduction 205 6.2 Introduction of Spray-Coating Method 206 6.2.1 History of Spray Coating 206 6.2.2 Spray-Coating Equipment 206 6.2.2.1 Airbrush Spray Deposition 206 6.2.2.2 Ultrasonic Spray Deposition 209 6.2.2.3 Electrospray Deposition 210 6.2.3 Spray-Coating Treatment 212 6.2.3.1 Thermal Annealing 213 6.2.3.2 Solvent Treatments 214 6.3 Materials for Spray Coating 216 6.3.1 Organic Materials 216 6.3.2 Metal Oxide and Nanoparticles 220 6.3.3 Perovskite 222 6.4 Application of Spray Coating 224 6.5 Conclusions 226 Acknowledgment 226 References 226 7 Interface Engineering: A Key Aspect for the Potential Commercialization of Printable Organic Photovoltaic Cells 235 Varun Vohra, Nur Tahirah Razali and Hideyuki Murata 7.1 Introduction 236 7.2 SD-PSCs Based on P3HT:PCBM Active Layers 240 7.2.1 Increase in Donor-Acceptor Interface through Nanostructuration of SD-PSCs 240 7.2.2 Generation of Vertical Concentration Gradient by Addition of Regiorandom P3HT in SD-PSCs 242 7.2.3 Generation of Vertical Concentration Gradient and Molecular Orientation by Rubbing P3HT in SD-PSCs 246 7.3 High Performance BHJ-PSCs with Favorable Molecular Orientation Resulting from Active Layer/Substrate Interactions 248 7.4 Strongly Bond Metal Leaves as Laminated Top Electrodes for Low-Cost PSC Fabrication 252 7.5 Conclusions 257 References 258 8 Structural, Optical, Electrical and Electronic Properties of PEDOT: PSS Thin Films and Their Application in Solar Cells 263 Sheng Hsiung Chang, Cheng-Chiang Chen, Hsin-Ming Cheng and Sheng-Hui Chen 8.1 Introduction 264 8.2 Chemical Structure of PEDOT:PSS 265 8.3 Optical and Electrical Characteristics of PEDOT:PSS 267 8.4 Electronic Characteristics of PEDOT:PSS 270 8.5 Highly Conductive PEDOT:PSS Thin Films 271 8.6 Hole-Transporting Materials: PEDOT:PSS Thin Films 273 8.6.1 Effect of PEDOT/PSS Ratio 274 8.6.2 Effect of Spin Rate 275 8.6.3 Effect of Thermal Annealing Temperature 277 8.6.4 Effects of Viscosity of PEDOT:PSS Solutions 278 8.7 Directions for Future Development 281 8.8 Conclusion 282 Reference 283 Part III Perovskites and Process Technologies for Printable Solar Cells 9 Organometal Trihalide Perovskite Absorbers: Optoelectronic Properties and Applications for Solar Cells 291 Timur Sh. Atabaev and Nguyen Hoa Hong 9.1 Introduction 291 9.2 Optical Properties of Organic-Inorganic Perovskite Materials 293 9.3 Charge Transport Properties 294 9.4 Electron Transporting Materials (ETM) 295 9.5 Hole-Transporting Materials (HTM) 295 9.6 Perovskite Solar Cells Architectures 296 9.7 Perovskite Deposition Methods 298 9.8 Photoexcited States 300 9.9 Hysteresis 300 9.10 Stability in Humid Environment 302 9.11 Stability Under UV Light Exposure 302 9.12 Stability at High Temperatures 303 9.13 Additives 304 9.14 Conclusions and Outlook 305 Acknowledgment 306 References 306 10 Organic-Inorganic Hybrid Perovskite Solar Cells with Scalable and Roll-to-Roll Compatible Printing/Coating Processes 313 Dechan Angmo, Mei Gao and Doojin Vak 10.1 Introduction 314 10.2 Optoelectronic Properties 316 10.3 History 317 10.4 Device Configurations 318 10.5 Functional Materials 321 10.5.1 The Organic-Inorganic Halide Perovskites 322 10.5.2 Electron-Selective Layer 324 10.5.3 Hole-Selective Layer 325 10.5.4 Transparent Electrode 325 10.5.5 Counter Electrode 326 10.6 Spin Coating 327 10.7 Roll-to-Roll Processing 331 10.8 Substrate Limitation 331 10.9 Printing and Coating Methods 333 10.9.1 Coating Methods 335 10.9.1.1 Slot-Die Coating 335 10.9.1.2 Spray Coating 339 10.9.1.3 Doctor Blade Coating 342 10.9.1.4 Knife Coating 344 10.9.1.5 Reverse Gravure Coating 345 10.9.2 Printing Methods 346 10.9.2.1 Gravure Printing 346 10.9.2.2 Flexographic Printing 347 10.9.2.3 Screen Printing 349 10.9.2.4 Inkjet Printing 350 10.10 Future Outlook 352 References 352 11 Inkjet Printable Processes for Dye-Sensitized and Perovskite Solar Cells and Modules Based on Advanced Nanocomposite Materials 363 Theodoros Makris, Argyroula Mourtzikou, Andreas Rapsomanikis and Elias Stathatos 11.1 Introduction 364 11.1.1 Dye-Sensitized Solar Cells 364 11.1.2 Perovskite Solar Cells 367 11.2 Inkjet Printing Process 369 11.2.1 Inkjet Printing in DSSC Technology 370 11.2.1.1 Inkjet Printing of Transition Metal Oxides 372 11.2.1.2 Inkjet Printing of Dyes on Semiconducting Oxides 373 11.2.1.3 Inkjet Printing of Ionic Liquid-Based Electrolytes 374 11.2.2 Inkjet Printing in Perovskite Solar Cell Technology 377 11.2.2.1 Inkjet Printing of Perovskite Material 378 11.3 Conclusions 379 References 379 Part IV Inorganic Materials and Process Technologies for Printable Solar Cells 383 12 Solution-Processed Kesterite Solar Cells 385 Fangyang Liu 12.1 Introduction 385 12.2 Fundamental Aspects of Kesterite Solar Cells 386 12.2.1 Crystal Structure 386 12.2.2 Phase Space and Secondary Phases 388 12.2.3 Optical and Electrical Properties 390 12.2.4 Device Architecture 391 12.3 Keterite Absorber Deposition Strategies 393 12.4 Electrodeposition 395 12.4.1 Stacked Elemental Layer (SEL) Electrodeposition 396 12.4.2 Metallic Alloy Co-electrodeposition 398 12.4.3 Chalcogenide Co-electrodeposition 399 12.5 Direct Solution Coating 400 12.5.1 Hydrazine Solution Coating 401 12.5.2 Particulate-Based Solution Coating 402 12.5.3 Molecular-Based Solution Coating 405 12.6 Conclusion 409 References 409 13 Inorganic Hole Contacts for Perovskite Solar Cells: Towards High-Performance Printable Solar Cells 423 Xingtian Yin and Wenxiu Que 13.1 Introduction 424 13.2 Transition Metal Oxides 426 13.2.1 Molybdenum Oxide (MoOx, x < 3) 426 13.2.2 Nickel Oxide (NiO) 428 13.2.2.1 Mesoscopic NiO Perovskite Solar Cells 428 13.2.2.2 Planar NiO Perovskite Solar Cells 429 13.2.3 Binary Copper Oxide (CuO and Cu2O) 439 13.2.4 Other Transition Metal Oxides 440 13.3 Non-Oxide Copper Compounds 440 13.3.1 Cuprous Iodide (CuI) 441 13.3.2 Cuprous Rhodanide (CuSCN) 441 13.3.3 Copper Sulfide (CuS) 442 13.3.4 CuAlO2 443 13.3.5 CuInS2 and Cu2ZnSnS4 444 13.4 Other Inorganic HTMs 444 13.4.1 PdS Quantum Dots (QDs) 444 13.4.2 Two-Dimensional (2D) Materials 445 13.5 Towards Printable Solar Cells 446 13.6 Conclusions and Perspectives 449 Acknowledgment 450 References 450 14 Electrode Materials for Printable Solar Cells 457 Lijun Hu, Ke Yang, Wei Chen, Falin Wu, Jiehao Fu, Wenbo Sun, Hongyan Huang, Baomin Zhao, Kuan Sun and Jianyong Ouyang 14.1 Introduction 458 14.2 Transparent Conjugated Polymers 459 14.2.1 Solvent Additive Method 460 14.2.2 Post-Treatment of PEDOT:PSS Films 461 14.2.3 Printing PEDOT:PSS Inks 463 14.3 Carbon-Based Nanomaterials 463 14.3.1 Graphene 466 14.3.2 Carbon Nanotubes 472 14.4 Metallic Nanostructures 476 14.4.1 Metal Nanomeshes 476 14.4.2 Metal Nanowire Networks 480 14.4.3 Ultrathin Metal Films 482 14.5 Multilayer Thin Films 486 14.6 Printable Metal Back Electrodes 491 14.7 Carbon-Based Back Electrodes 494 14.8 Summary and Outlook 497 Acknowledgment 498 References 498 15 Photonic Crystals for Photon Management in Solar Cells 513 Shuai Zhang, Zhongze Gu and Jian-Ning Ding 15.1 Introduction 513 15.2 Fundamentals of PCs 515 15.3 Fabrication Strategies of PCs for Photovoltaics 518 15.3.1 1D Multilayer PCs 519 15.3.2 2D PCs 524 15.3.3 3D PCs 527 15.4 Different Functionalities of PCs in Solar Cells 530 15.4.1 PC Reflectors 531 15.4.2 PC Absorbers 535 15.4.3 Front-Side PCs 538 15.4.4 PCs for Other Functionalities 540 15.5 Summary and Outlook 540 Acknowledgment 542 References 542

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Book SynopsisA comprehensive, step-by-step reference to the Nyström Method for solving Electromagnetic problems using integral equations Computational electromagnetics studies the numerical methods or techniques that solve electromagnetic problems by computer programming. Currently, there are mainly three numerical methods for electromagnetic problems: the finite-difference time-domain (FDTD), finite element method (FEM), and integral equation methods (IEMs). In the IEMs, the method of moments (MoM) is the most widely used method, but much attention is being paid to the Nyström method as another IEM, because it possesses some unique merits which the MoM lacks. This book focuses on that methodproviding information on everything that students and professionals working in the field need to know. Written by the top researchers in electromagnetics, this complete reference book is a consolidation of advances made in the use of the Nyström method for solving electromagnetic integral equations. It beginTable of ContentsAbout the Authors xiii Preface xv Acknowledgment xxi 1 Electromagnetics, Physics, and Mathematics 1 1.1 A Brief History of Electromagnetics 1 1.2 Enduring Legacy of Electromagnetic Theory–Why? 3 1.3 The Rise of Quantum Optics and Electromagnetics 4 1.3.1 Connection of Quantum Electromagnetics to Classical Electromagnetics 5 1.4 The Early Days – Descendent from Fluid Physics 6 1.5 The Complete Development of Maxwell’s Equations 7 1.5.1 Derivation of Wave Equation 9 1.6 Circuit Physics,Wave Physics, Ray Physics, and Plasmonic Resonances 10 1.6.1 Circuit Physics 10 1.6.2 Wave Physics 14 1.6.3 Ray Physics 15 1.6.4 Plasmonic Resonance 17 1.7 The Age of Closed Form Solutions 20 1.7.1 Separable Coordinate Systems 20 1.7.2 Integral Transform Solution 21 1.8 The Age of Approximations 23 1.8.1 Asymptotic Expansions 23 1.8.2 Matched Asymptotic Expansions 24 1.8.3 Ansatz-Based Approximations 27 1.9 The Age of Computations 28 1.9.1 Computations and Mathematics 30 1.9.2 Sobolev Space and Dual Space 33 1.10 Fast Algorithms 35 1.10.1 Cruelty of Computational Complexity 36 1.10.2 Curse of Dimensionality 38 1.10.3 Multiscale Problems 38 1.10.4 Fast Algorithm for Multiscale Problems 39 1.10.5 Domain Decomposition Methods 40 1.11 High Frequency Solutions 41 1.12 Inverse Problems 41 1.12.1 Distorted Born Iterative Method 42 1.12.2 Super-Resolution Reconstruction 43 1.12.3 Super-Resolution and the Weyl-Sommerfeld Identity 43 1.13 Metamaterials 46 1.14 Small Antennas 47 1.15 Conclusions 48 Bibliography 49 2 Computational Electromagnetics 75 2.1 Introduction 75 2.2 Analytical Methods 77 2.3 Numerical Methods 82 2.3.1 The Finite-Difference Time-Domain (FDTD)Method 83 2.3.2 The Finite Element Method (FEM) 83 2.3.3 The Method of Moments (MoM) 84 2.4 Electromagnetic Integral Equations 87 2.4.1 Surface Integral Equations (SIEs) 88 2.4.2 Volume Integral Equations (VIEs) 91 2.4.3 Volume-Surface Integral Equations (VSIEs) 93 2.5 Summary 95 Bibliography 95 3 The Nyström Method 99 3.1 Introduction 99 3.2 Basic Principle 100 3.3 Singularity Treatment 101 3.4 Higher-Order Scheme 102 3.5 Comparison to the Method of Moments 103 3.6 Comparison to the Point-Matching Method 104 3.7 Summary 105 Bibliography 106 4 Numerical Quadrature Rules 107 4.1 Introduction 107 4.2 Definition and Design 108 4.3 Quadrature Rules for a Segmental Mesh 108 4.4 Quadrature Rules for a Surface Mesh 109 4.4.1 Quadrature Rules for a Triangular Patch 109 4.4.2 Quadrature Rules for a Square Patch 112 4.5 Quadrature Rules for a Volumetric Mesh 116 4.5.1 Quadrature Rules for a Tetrahedral Element 116 4.5.2 Quadrature Rules for a Cuboid Element 121 4.6 Summary 122 Bibliography 123 5 Singularity Treatment 125 5.1 Introduction 125 5.2 Singularity Subtraction 126 5.2.1 Basic Principle 126 5.2.2 Subtraction for the Kernel of ; Operator 127 5.2.3 Subtraction for the Kernel of ; Operator 130 5.2.4 Subtraction for the Kernels of VIEs 132 5.3 Singularity Cancellation 133 5.3.1 Surface Integral Equation 134 5.3.2 Evaluation of the Weakly-Singular Integrals 135 5.3.3 Numerical Examples 138 5.4 Evaluation of Hypersingular and Weakly-Singular Integrals over Triangular Patches 143 5.4.1 Hypersingular Integrals 144 5.4.2 Weakly-Singular Integrals 149 5.4.3 Non-Singular Integrals 152 5.4.4 Numerical Examples 154 5.5 Different Scheme for Evaluating Strongly-Singular and Hypersingular Integrals Over Triangular Patches 154 5.5.1 Strongly-Singular and Hypersingular Integrals 157 5.5.2 Stokes’ Theorem 159 5.5.3 Derivation of New Formulas for HSIs and SSIs 160 5.5.4 Numerical Tests 164 5.5.5 Numerical Examples 164 5.6 Evaluation of Singular Integrals Over Volume Domains 167 5.6.1 Representation of Volume Current Density 168 5.6.2 Evaluation of Singular Integrals 169 5.6.3 Numerical Examples 172 5.7 Evaluation of Near-Singular Integrals 176 5.7.1 Integral Equations and Near-Singular Integrals 177 5.7.2 Evaluation 179 5.7.3 Numerical Examples 185 5.8 Summary 187 Bibliography 188 6 Application to Conducting Media 193 6.1 Introduction 193 6.2 Solution for 2D Structures 193 6.2.1 General 2D Structures 194 6.2.2 2D Open Structures with Edge Conditions 196 6.2.3 Evaluation of Singular and Near-Singular Integrations 199 6.2.4 Numerical Examples 204 6.3 Solution for Body-of-Revolution (BOR) Structures 211 6.3.1 2D Integral Equations 212 6.3.2 Evaluation of Singular Fourier Expansion Coefficients 215 6.3.3 Numerical Examples 219 6.4 Solutions of the Electric Field Integral Equation 221 6.4.1 Higher-order Nyström method 222 6.4.2 Numerical Examples 225 6.5 Solutions of the Magnetic Field Integral Equation 228 6.5.1 Integral Equations 229 6.5.2 Singularity and Near-Singularity Treatment 230 6.5.3 Numerical Examples 233 6.6 Solutions of the Combined Field Integral Equation 238 6.6.1 Integral Equations 239 6.6.2 Quality of Triangular Patches 240 6.6.3 Nyström Discretization 241 6.6.4 Numerical Examples 242 6.7 Summary 245 Bibliography 246 7 Application to Penetrable Media 253 7.1 Introduction 253 7.2 Surface Integral Equations for Homogeneous and Isotropic Media 254 7.2.1 Surface Integral Equations 254 7.2.2 Nyström Discretization 259 7.2.3 Numerical Examples 260 7.3 Volume Integral Equations for Homogeneous and Isotropic Media 266 7.3.1 Volume Integral Equations 268 7.3.2 Nyström Discretization 268 7.3.3 Local Correction Scheme 271 7.3.4 Numerical Examples 274 7.4 Volume Integral Equations for Inhomogeneous or/and Anisotropic Media 279 7.4.1 Volume Integral Equations 280 7.4.2 Inconvenience of the Method of Moments 282 7.4.3 Nyström Discretization 283 7.4.4 Numerical Examples 284 7.5 Volume Integral Equations for Conductive Media 287 7.5.1 Volume Integral Equations 289 7.5.2 Nyström Discretization 290 7.5.3 Numerical Examples 291 7.6 Volume-Surface Integral Equations for Mixed Media 296 7.6.1 Volume-Surface Integral Equations 298 7.6.2 Nyström-Based Mixed Scheme for Solving the VSIEs 299 7.6.3 Numerical Examples 301 7.7 Summary 306 Bibliography 309 8 Incorporation with Multilevel Fast Multipole Algorithm 317 8.1 Introduction 317 8.2 Multilevel Fast Multipole Algorithm 318 8.3 Surface Integral Equations for Conducting Objects 320 8.3.1 Integral Equations 321 8.3.2 Nyström Discretization and MLFMA Acceleration 321 8.3.3 Numerical Examples 323 8.4 Surface Integral Equations for Penetrable Objects 325 8.4.1 Integral Equations 327 8.4.2 MLFMA Acceleration 329 8.4.3 Numerical Examples 331 8.5 Volume Integral Equations for Conductive Media 335 8.5.1 Integral Equations 336 8.5.2 Nyström Discretization 337 8.5.3 Incorporation with the MLFMA 338 8.5.4 Numerical Examples 338 8.6 Volume-Surface Integral Equations for Conducting-Anisotropic Media 342 8.6.1 Integral Equations for Anisotropic Objects 343 8.6.2 Nyström Discretization 344 8.6.3 MLFMA Acceleration 345 8.6.4 Numerical Examples 347 8.7 Summary 352 Bibliography 353 9 Application to Solve Multiphysics Problems 357 9.1 Introduction 357 9.2 Solution of Elastic Wave Problems 359 9.2.1 Boundary Integral Equations 359 9.2.2 Singularity Treatment 362 9.2.3 Numerical Examples 364 9.3 MLFMA Acceleration for Solve Large Elastic Wave Problems 369 9.3.1 Formulations 370 9.3.2 Reformulation of Near Terms 375 9.3.3 Reduction of Number of Patterns 377 9.3.4 Numerical Examples 379 9.4 Solution of Acoustic Wave Problems with MLFMA Acceleration 383 9.4.1 Implementation of the MLFMA for the Acoustic BIE 383 Acoustic BIE 384 Radiation and Receiving Patterns 384 Near Terms 385 9.4.2 Numerical Examples 388 9.5 Unified Boundary Integral Equations for Elastic Wave and Acoustic Wave 395 9.5.1 Elastic Wave BIEs 397 9.5.2 Limit of Dyadic Green’s Function 398 9.5.3 Vector BIE for Acoustic Wave 399 9.5.4 Method of Moments (MoM) Solutions 401 9.5.5 Numerical Examples 403 9.6 Coupled Integral Equations for Electromagnetic Wave and Elastic Wave 411 9.6.1 EM Wave Integral Equations 412 9.6.2 Elastic Wave Integral Equations 415 9.6.3 Coupled Integral Equations 418 9.6.4 Solving Method 420 9.6.5 Numerical Examples 421 9.7 Summary 425 Bibliography 429 10 Application to Solve Time Domain Integral Equations 437 10.1 Introduction 437 10.2 Time Domain Surface Integral Equations for Conducting Media 438 10.2.1 Time Domain Electric Field Integral Equation 438 Formulations 439 Numerical Solution 440 Numerical Examples 442 10.2.2 Time Domain Magnetic Field Integral Equation 446 Formulations 447 Numerical Solution 447 Numerical Examples 449 10.3 Time Domain Surface Integral Equations for Penetrable Media 454 10.3.1 Formulations 455 10.3.2 Numerical Solution 456 10.3.3 Numerical Examples 459 10.4 Time Domain Volume Integral Equations for Penetrable Media 465 10.4.1 Formulations 466 10.4.2 Numerical Solution 467 10.4.3 Numerical Examples 470 10.5 Time Domain Combined Field Integral Equations for Mixed Media 476 10.5.1 Formulations 476 10.5.2 Numerical Solution 479 10.5.3 Numerical Examples 484 10.6 Summary 488 Bibliography 488 Index 493

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Book SynopsisAn accessible introduction to probability, stochastic processes, and statistics for computer science and engineering applicationsSecond edition now also available in Paperback. This updated and revised edition of the popular classic first edition relates fundamental concepts in probability and statistics to the computer sciences and engineering. The author uses Markov chains and other statistical tools to illustrate processes in reliability of computer systems and networks, fault tolerance, and performance.This edition features an entirely new section on stochastic Petri netsas well as new sections on system availability modeling, wireless system modeling, numerical solution techniques for Markov chains, and software reliability modeling, among other subjects. Extensive revisions take new developments in solution techniques and applications into account and bring this work totally up to date. It includes more than 200 worked examples and self-study exerciTrade Review"The book offers a comprehensive introduction to probability, stochastic processes, and statistics for students of computer science, electrical and computer engineering, and applied mathematics. Its wealth of practical examples and up-to-date information makes it an excellent resource for practitioners as well." (Zentralblatt MATH, 2016) "I highly recommend this book for academics for use as a textbook and for researchers and professionals in the field as a useful reference." (Interfaces, September/ October 2004) "This introduction...uses Markov chains and other statistical tools to illustrate process in reliability of computer systems, fault tolerance, and performance." (SciTech Book News, Vol. 26, No. 2, June 2002) "...an excellent self-contained book.... I recommend the book to beginners and veterans in the field..." (Computer Journal, Vol.45, No.6, 2002) "This book is a tour de force of clear, virtually error-free exposition of probability as it is applied in a host of up-to-date contexts.... It will richly reward the...reader.... Read this book cover to cover. It’s worth the effort." (Technometrics, Vol. 45, No. 1, February 2003)Table of ContentsPreface to the Paperback Edition ix Preface to the Second Edition xi Preface to the First Edition xiii Acronyms xv About the Companion Website xix 1 Introduction 1 1.1 Motivation 1 1.2 Probability Models 2 1.3 Sample Space 3 1.4 Events 6 1.5 Algebra of Events 7 1.6 Graphical Methods of Representing Events 11 1.7 Probability Axioms 13 1.8 Combinatorial Problems 19 1.9 Conditional Probability 24 1.10 Independence of Events 26 1.11 Bayes’ Rule 38 1.12 Bernoulli Trials 47 2 Discrete Random Variables 65 2.1 Introduction 65 2.2 Random Variables and Their Event Spaces 66 2.3 The Probability Mass Function 68 2.4 Distribution Functions 70 2.5 Special Discrete Distributions 72 2.6 Analysis of Program MAX 97 2.7 The Probability Generating Function 101 2.8 Discrete Random Vectors 104 2.9 Independent Random Variables 110 3 Continuous Random Variables 121 3.1 Introduction 121 3.2 The Exponential Distribution 125 3.3 The Reliability and Failure Rate 130 3.4 Some Important Distributions 135 3.5 Functions of a Random Variable 154 3.6 Jointly Distributed Random Variables 159 3.7 Order Statistics 163 3.8 Distribution of Sums 174 3.9 Functions of Normal Random Variables 190 4 Expectation 201 4.1 Introduction 201 4.2 Moments 205 4.3 Expectation Based on Multiple Random Variables 209 4.4 Transform Methods 216 4.5 Moments and Transforms of Some Distributions 226 4.6 Computation of Mean Time to Failure 238 4.7 Inequalities and Limit Theorems 247 5 Conditional Distribution and Expectation 257 5.1 Introduction 257 5.2 Mixture Distributions 266 5.3 Conditional Expectation 273 5.4 Imperfect Fault Coverage and Reliability 280 5.5 Random Sums 290 6 Stochastic Processes 301 6.1 Introduction 301 6.2 Classification of Stochastic Processes 307 6.3 The Bernoulli Process 313 6.4 The Poisson Process 317 6.5 Renewal Processes 327 6.6 Availability Analysis 332 6.7 Random Incidence 342 6.8 Renewal Model of Program Behavior 346 7 Discrete-Time Markov Chains 351 7.1 Introduction 351 7.2 Computation of n-step Transition Probabilities 356 7.3 State Classification and Limiting Probabilities 362 7.4 Distribution of Times Between State Changes 371 7.5 Markov Modulated Bernoulli Process 373 7.6 Irreducible Finite Chains with Aperiodic States 376 7.7 The M/G/ 1 Queuing System 391 7.8 Discrete-Time Birth–Death Processes 400 7.9 Finite Markov Chains with Absorbing States 407 8 Continuous-Time Markov Chains 421 8.1 Introduction 421 8.2 The Birth–Death Process 428 8.3 Other Special Cases of the Birth–Death Model 465 8.4 Non-Birth–Death Processes 474 8.5 Markov Chains with Absorbing States 519 8.6 Solution Techniques 541 8.7 Automated Generation 552 9 Networks of Queues 577 9.1 Introduction 577 9.2 Open Queuing Networks 582 9.3 Closed Queuing Networks 590 9.4 General Service Distribution and Multiple Job Types 620 9.5 Non-product-form Networks 628 9.6 Computing Response Time Distribution 641 9.7 Summary 654 10 Statistical Inference 661 10.1 Introduction 661 10.2 Parameter Estimation 663 10.3 Hypothesis Testing 718 11 Regression and Analysis of Variance 753 11.1 Introduction 753 11.2 Least-squares Curve Fitting 758 11.3 The Coefficients of Determination 762 11.4 Confidence Intervals in Linear Regression 765 11.5 Trend Detection and Slope Estimation 768 11.6 Correlation Analysis 771 11.7 Simple Nonlinear Regression 774 11.8 Higher-dimensional Least-squares Fit 775 11.9 Analysis of Variance 778 A Bibliography 791 A.1 Theory 791 A.2 Applications 796 B Properties of Distributions 804 C Statistical Tables 807 D Laplace Transforms 828 E Program Performance Analysis 835 Author Index 837 Subject Index 845

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Book SynopsisOffers the first comprehensive account of this interesting and growing research field Printed Batteries: Materials, Technologies and Applications reviews the current state of the art for printed batteries, discussing the different types and materials, and describing the printing techniques. It addresses the main applications that are being developed for printed batteries as well as the major advantages and remaining challenges that exist in this rapidly evolving area of research. It is the first book on printed batteries that seeks to promote a deeper understanding of this increasingly relevant research and application area. It is written in a way so as to interest and motivate readers to tackle the many challenges that lie ahead so that the entire research community can provide the world with a bright, innovative future in the area of printed batteries. Topics covered in Printed Batteries include, Printed Batteries: Definition, Types and AdvantageTable of Contents1 Printed Batteries: An Overview 1Juliana Oliveira, Carlos Miguel Costa and Senentxu Lanceros-Méndez 1.1 Introduction 1 1.2 Types of Printed Batteries 7 1.3 Design of Printed Batteries 9 1.4 Main Advantages and Disadvantages of Printed Batteries 11 1.4.1 Advantages 11 1.4.2 Disadvantages 12 1.5 Application Areas 13 1.6 Commercial Printed Batteries 14 1.7 Summary and Outlook 14 Acknowledgements 15 References 16 2 Printing Techniques for Batteries 21Andreas Willert, Anh-Tuan Tran-Le, Kalyan Yoti Mitra, Maurice Clair, Carlos Miguel Costa, Senentxu Lanceros-Méndez and Reinhard Baumann 2.1 Introduction/Abstract 21 2.2 Materials and Substrates 22 2.3 Printing Techniques 23 2.3.1 Screen Printing 25 2.3.1.1 Flatbed 25 2.3.1.2 Rotary 27 2.3.1.3 Screen Mesh 28 2.3.1.4 Squeegee 29 2.3.2 Stencil Printing 30 2.3.3 Flexographic Printing 31 2.3.3.1 Letterpress Printing 31 2.3.3.2 Flexography 32 2.3.4 Gravure Printing 33 2.3.5 Lithographic/Offset Printing 35 2.3.6 Coating 36 2.3.7 Inkjet 38 2.3.7.1 Inkjet Printing Technology and Applications 38 2.3.7.2 Selective View of the Market for Inkjet Technology 44 2.3.7.3 Advanced Applications: Printed Functionalities and Electronics 48 2.3.8 Drying Process 50 2.3.9 Process Chain 52 2.3.10 Printing of Layers 53 2.4 Conclusions 54 Acknowledgements 54 References 55 3 The Influence of Slurry Rheology on Lithium-ion Electrode Processing 63Ta]Jo Liu, Carlos Tiu, Li-Chun Chen and Darjen Liu 3.1 Introduction 63 3.2 Slurry Formulation 64 3.3 Rheological Characteristics of Electrode Slurry 65 3.3.1 Viscosity and Shear-Thinning 65 3.3.2 Viscoelasticity 66 3.3.3 Yield Stress 68 3.4 Effects of Rheology on Electrode Processing 69 3.4.1 Composition of Electrode Slurry 69 3.4.2 Electrode Slurry Preparation 70 3.4.2.1 Mixing Methods 70 3.4.2.2 Mixing Devices 73 3.4.3 Electrode Coating 75 3.4.4 Electrode Drying 75 3.5 Conclusion 76 List of Symbols and Abbreviations 76 References 76 4 Polymer Electrolytes for Printed Batteries 80Ela Strauss, Svetlana Menkin and Diana Golodnitsky 4.1 Electrolytes for Conventional Batteries 80 4.1.1 Polymer/Gel Electrolytes for Aqueous Batteries 81 4.1.2 Electrolytes for Lithium-ion Batteries 82 4.2 Electrolytes for Printed Batteries 84 4.2.1 Screen-printed Electrolytes 85 4.2.2 Spray-printed Electrolytes 86 4.2.3 Direct-write Printed Electrolytes 88 4.2.4 Laser-printed Electrolytes 99 4.3 Summary 107 References 108 5 Design of Printed Batteries: From Chemistry to Aesthetics 112Keun-Ho Choi and Sang-Young Lee 5.1 Introduction 112 5.2 Design of Printed Battery Components 114 5.2.1 Printed Electrodes 114 5.2.2 Printed Separator Membranes and Solid-state Electrolytes 121 5.3 Aesthetic Versatility of Printed Battery Systems 126 5.3.1 Zn/MnO2 Batteries 126 5.3.2 Supercapacitors 132 5.3.3 Li-ion Batteries 134 5.3.4 Other Systems 138 5.4 Summary and Prospects 138 Acknowledgements 141 References 141 6 Applications of Printed Batteries 144Abhinav M. Gaikwad, Aminy E. Ostfeld and Ana Claudia Arias 6.1 Printed Microbatteries 146 6.2 Printed Primary Batteries 151 6.3 Printed Rechargeable Batteries 160 6.4 High-Performance Printed Structured Batteries 169 6.5 Power Electronics and Energy Harvesting 174 References 182 7 Industrial Perspective on Printed Batteries 185Patrick Rassek, Michael Wendler and Martin Krebs 7.1 Introduction 185 7.2 Printing Technologies for Functional Printing 186 7.2.1 Flexography 188 7.2.2 Gravure Printing 190 7.2.3 Offset Printing 192 7.2.4 Screen Printing 193 7.2.5 Conclusion 197 7.3 Comparison of Conventional Battery Manufacturing Methods with Screen Printing Technology 197 7.4 Industrial Aspects of Screen-printed Thin Film Batteries 200 7.4.1 Layout Considerations 200 7.4.1.1 Sandwich Architecture (Stack Configuration) 200 7.4.1.2 Parallel Architecture (Coplanar Configuration) 201 7.4.2 Carrier Substrates and Multifunctional Substrates for Printed Batteries 203 7.4.2.1 Barrier Requirements and Material Selection 205 7.4.2.2 Process Requirements of Qualified Materials 206 7.4.3 Current Collectors 209 7.4.4 Electrodes 210 7.4.5 Electrolytes and Separator 214 7.4.6 Encapsulation Technologies 215 7.4.6.1 Screen Printing of Adhesives 215 7.4.6.2 Contact Heat Sealing 216 7.4.6.3 Ultrasonic Welding 217 7.4.7 Conclusion 219 7.5 Industrial Applications and Combination With Other Flexible Electronic Devices 220 7.5.1 Self-powered Temperature Loggers 220 7.5.2 Smart Packaging Devices 222 7.6 Industrial Perspective on Printed Batteries 223 7.6.1 Competition with Conventional Batteries 223 7.6.2 Cold Chain Monitoring 225 7.6.3 Health]monitoring Devices 226 7.7 Conclusion 226 References 227 8 Open Questions, Challenges and Outlook 230Carlos Miguel Costa, Juliana Oliveira and Senentxu Lanceros-Méndez Acknowledgements 233 References 233 Index 235

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Book SynopsisDemonstrates how to solve reliability problems using practical applications of Bayesian models This self-contained reference provides fundamental knowledge of Bayesian reliability and utilizes numerous examples to show how Bayesian models can solve real life reliability problems. It teaches engineers and scientists exactly what Bayesian analysis is, what its benefits are, and how they can apply the methods to solve their own problems. To help readers get started quickly, the book presents many Bayesian models that use JAGS and which require fewer than 10 lines of command. It also offers a number of short R scripts consisting of simple functions to help them become familiar with R coding. Practical Applications of Bayesian Reliability starts by introducing basic concepts of reliability engineering, including random variables, discrete and continuous probability distributions, hazard function, and censored data. Basic concepts of Bayesian statistics, models, reasons, and theory are prTable of ContentsPreface xi Acknowledgments xv About the Companion Website xvii 1 Basic Concepts of Reliability Engineering 1 1.1 Introduction 1 1.1.1 Reliability Definition 3 1.1.2 Design for Reliability and Design for Six Sigma 4 1.2 Basic Theory and Concepts of Reliability Statistics 5 1.2.1 Random Variables 5 1.2.2 Discrete Probability Distributions 6 1.2.3 Continuous Probability Distributions 6 1.2.4 Properties of Discrete and Continuous Random Variables 6 1.2.4.1 Probability Mass Function 6 1.2.4.2 Probability Density Function 7 1.2.4.3 Cumulative Distribution Function 8 1.2.4.4 Reliability or Survival Function 8 1.2.4.5 Hazard Rate or Instantaneous Failure Rate 9 1.2.4.6 Cumulative Hazard Function 10 1.2.4.7 The Average Failure Rate Over Time 10 1.2.4.8 Mean Time to Failure 10 1.2.4.9 Mean Number of Failures 11 1.2.5 Censored Data 11 1.2.6 Parametric Models of Time to Failure Data 13 1.2.7 Nonparametric Estimation of Survival 14 1.2.8 Accelerated Life Testing 16 1.3 Bayesian Approach to Reliability Inferences 18 1.3.1 Brief History of Bayes’ Theorem and Bayesian Statistics 18 1.3.2 How Does Bayesian Statistics Relate to Other Advances in the Industry? 19 1.3.2.1 Advancement of Predictive Analytics 20 1.3.2.2 Cost Reduction 20 1.4 Component Reliability Estimation 20 1.5 System Reliability Estimation 20 1.6 Design Capability Prediction (Monte Carlo Simulations) 21 1.7 Summary 22 References 23 2 Basic Concepts of Bayesian Statistics and Models 25 2.1 Basic Idea of Bayesian Reasoning 25 2.2 Basic Probability Theory and Bayes’ Theorem 26 2.3 Bayesian Inference (Point and Interval Estimation) 32 2.4 Selection of Prior Distributions 35 2.4.1 Conjugate Priors 35 2.4.2 Informative and Non-informative Priors 38 2.5 Bayesian Inference vs. Frequentist Inference 44 2.6 How Bayesian Inference Works with Monte Carlo Simulations 48 2.7 Bayes Factor and its Applications 50 2.8 Predictive Distribution 53 2.9 Summary 57 References 57 3 Bayesian Computation 59 3.1 Introduction 59 3.2 Discretization 60 3.3 Markov Chain Monte Carlo Algorithms 66 3.3.1 Markov Chains 67 3.3.1.1 Monte Carlo Error 67 3.3.2 Metropolis–Hastings Algorithm 68 3.3.3 Gibbs Sampling 80 3.4 Using BUGS/JAGS 85 3.4.1 Define a JAGS Model 86 3.4.2 Create, Compile, and Run the JAGS Model 89 3.4.3 MCMC Diagnostics and Output Analysis 91 3.4.3.1 Summary Statistics 91 3.4.3.2 Trace Plots 92 3.4.3.3 Autocorrelation Plots 93 3.4.3.4 Cross-Correlation 93 3.4.3.5 Gelman–Rubin Diagnostic and Plots 94 3.4.4 Sensitivity to the Prior Distributions 95 3.4.5 Model Comparison 96 3.5 Summary 98 References 98 4 Reliability Distributions (Bayesian Perspective) 101 4.1 Introduction 101 4.2 Discrete Probability Models 102 4.2.1 Binomial Distribution 102 4.2.2 Poisson Distribution 104 4.3 Continuous Models 108 4.3.1 Exponential Distribution 108 4.3.2 Gamma Distribution 113 4.3.3 Weibull Distribution 115 4.3.3.1 Fit Data to a Weibull Distribution 116 4.3.3.2 Demonstrating Reliability using Right-censored Data Only 120 4.3.4 Normal Distribution 135 4.3.5 Lognormal Distribution 139 4.4 Model and Convergence Diagnostics 143 References 143 5 Reliability Demonstration Testing 145 5.1 Classical Zero-failure Test Plans for Substantiation Testing 146 5.2 Classical Zero-failure Test Plans for Reliability Testing 147 5.3 Bayesian Zero-failure Test Plan for Substantiation Testing 149 5.4 Bayesian Zero-failure Test Plan for Reliability Testing 161 5.5 Summary 162 References 163 6 Capability and Design for Reliability 165 6.1 Introduction 165 6.2 Monte Caro Simulations with Parameter Point Estimates 166 6.2.1 Stress-strength Interference Example 166 6.2.2 Tolerance Stack-up Example 171 6.3 Nested Monte Carlo Simulations with Bayesian Parameter Estimation 174 6.3.1 Stress-strength Interference Example 175 6.3.2 Tolerance Stack-up Example 182 6.4 Summary 186 References 186 7 System Reliability Bayesian Model 187 7.1 Introduction 187 7.2 Reliability Block Diagram 188 7.3 Fault Tree 196 7.4 Bayesian Network 197 7.4.1 A Multiple-sensor System 199 7.4.2 Dependent Failure Modes 202 7.4.3 Case Study: Aggregating Different Sources of Imperfect Data 204 7.5 Summary 214 References 214 8 Bayesian Hierarchical Model 217 8.1 Introduction 217 8.2 Bayesian Hierarchical Binomial Model 221 8.2.1 Separate One-level Bayesian Models 221 8.2.2 Bayesian Hierarchical Model 222 8.3 Bayesian Hierarchical Weibull Model 228 8.4 Summary 238 References 238 9 Regression Models 239 9.1 Linear Regression 239 9.2 Binary Logistic Regression 246 9.3 Case Study: Defibrillation Efficacy Analysis 257 9.4 Summary 277 References 278 Appendix A Guidance for Installing R, R Studio, JAGS, and rjags 279 A.1 Install R 279 A.2 Install R Studio 279 A.3 Install JAGS 280 A.4 Install Package rjags 280 A.5 Set Working Directory 280 Appendix B Commonly Used R Commands 281 B.1 How to Run R Commands 281 B.2 General Commands 281 B.3 Generate Data 282 B.4 Variable Types 283 B.5 Calculations and Operations 285 B.6 Summarize Data 286 B.7 Read and Write Data 287 B.8 Plot Data 288 B.9 Loops and Conditional Statements 290 Appendix C Probability Distributions 291 C.1 Discrete Distributions 291 C.1.1 Binomial Distribution 291 C.1.2 Poisson Distribution 291 C.2 Continuous Distributions 292 C.2.1 Beta Distribution 292 C.2.2 Exponential Distribution 292 C.2.3 Gamma Distribution 292 C.2.4 Inverse Gamma Distribution 293 C.2.5 Lognormal Distribution 293 C.2.6 Normal Distribution 293 C.2.7 Uniform Distribution 294 C.2.8 Weibull Distribution 294 Appendix D Jeffreys Prior 295 Index 299

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Book SynopsisHandbook of Software Fault Localization A comprehensive analysis of fault localization techniques and strategies In Handbook of Software Fault Localization: Foundations and Advances, distinguished computer scientists Prof. W. Eric Wong and Prof. T.H. Tse deliver a robust treatment of up-to-date techniques, tools, and essential issues in software fault localization. The authors offer collective discussions of fault localization strategies with an emphasis on the most important features of each approach. The book also explores critical aspects of software fault localization, like multiple bugs, successful and failed test cases, coincidental correctness, faults introduced by missing code, the combination of several fault localization techniques, ties within fault localization rankings, concurrency bugs, spreadsheet fault localization, and theoretical studies on fault localization. Readers will benefit from the authors' straightforward discussions of how to aTable of ContentsEditor Biographies xv List of Contributors xvii 1 Software Fault Localization: an Overview of Research, Techniques, and Tools 1 W. Eric Wong, Ruizhi Gao, Yihao Li, Rui Abreu, Franz Wotawa, and Dongcheng li 1.1 Introduction 1 1.2 Traditional Fault Localization Techniques 14 1.2.1 Program Logging 14 1.2.2 Assertions 14 1.2.3 Breakpoints 14 1.2.4 Profiling 15 1.3 Advanced Fault Localization Techniques 15 1.3.1 Slicing-Based Techniques 15 1.3.2 Program Spectrum-Based Techniques 20 1.3.2.1 Notation 20 1.3.2.2 Techniques 21 1.3.2.3 Issues and Concerns 27 1.3.3 Statistics-Based Techniques 30 1.3.4 Program State-Based Techniques 32 1.3.5 Machine Learning-Based Techniques 34 1.3.6 Data Mining-Based Techniques 36 1.3.7 Model-Based Techniques 37 1.3.8 Additional Techniques 41 1.3.9 Distribution of Papers in Our Repository 45 1.4 Subject Programs 47 1.5 Evaluation Metrics 50 1.6 Software Fault Localization Tools 53 1.7 Critical Aspects 58 1.7.1 Fault Localization with Multiple Bugs 58 1.7.2 Inputs, Outputs, and Impact of Test Cases 60 1.7.3 Coincidental Correctness 63 1.7.4 Faults Introduced by Missing Code 64 1.7.5 Combination of Multiple Fault Localization Techniques 65 1.7.6 Ties Within Fault Localization Rankings 67 1.7.7 Fault Localization for Concurrency Bugs 67 1.7.8 Spreadsheet Fault Localization 68 1.7.9 Theoretical Studies 70 1.8 Conclusion 71 Notes 73 References 73 2 Traditional Techniques for Software Fault Localization 119 Yihao Li, Linghuan Hu, W. Eric Wong, Vidroha Debroy, and Dongcheng li 2.1 Program Logging 119 2.2 Assertions 121 2.3 Breakpoints 124 2.4 Profiling 125 2.5 Discussion 128 2.6 Conclusion 130 References 131 3 Slicing-Based Techniques for Software Fault Localization 135 W. Eric Wong, Hira Agrawal, and Xiangyu Zhang 3.1 Introduction 135 3.2 Static Slicing-Based Fault Localization 136 3.2.1 Introduction 136 3.2.2 Program Slicing Combined with Equivalence Analysis 137 3.2.3 Further Application 138 3.3 Dynamic Slicing-Based Fault Localization 138 3.3.1 Dynamic Slicing and Backtracking Techniques 144 3.3.2 Dynamic Slicing and Model-Based Techniques 145 3.3.3 Critical Slicing 148 3.3.3.1 Relationships Between Critical Slices (CS) and Exact Dynamic Program Slices (DPS) 149 3.3.3.2 Relationship Between Critical Slices and Executed Static Program Slices 150 3.3.3.3 Construction Cost 150 3.3.4 Multiple-Points Dynamic Slicing 151 3.3.4.1 BwS of an Erroneous Computed Value 152 3.3.4.2 FwS of Failure-Inducing Input Difference 152 3.3.4.3 BiS of a Critical Predicate 154 3.3.4.4 MPSs: Dynamic Chops 157 3.3.5 Execution Indexing 158 3.3.5.1 Concepts 159 3.3.5.2 Structural Indexing 161 3.3.6 Dual Slicing to Locate Concurrency Bugs 165 3.3.6.1 Trace Comparison 165 3.3.6.2 Dual Slicing 168 3.3.7 Comparative Causality: a Causal Inference Model Based on Dual Slicing 173 3.3.7.1 Property One: Relevance 174 3.3.7.2 Property Two: Sufficiency 175 3.3.8 Implicit Dependences to Locate Execution Omission Errors 177 3.3.9 Other Dynamic Slicing-Based Techniques 179 3.4 Execution Slicing-Based Fault Localization 179 3.4.1 Fault Localization Using Execution Dice 179 3.4.2 A Family of Fault Localization Heuristics Based on Execution Slicing 181 3.4.2.1 Heuristic I 182 3.4.2.2 Heuristic II 183 3.4.2.3 Heuristic III 185 3.4.3 Effective Fault Localization Based on Execution Slices and Inter-block Data Dependence 188 3.4.3.1 Augmenting a Bad D(1) 189 3.4.3.2 Refining a Good D(1) 190 3.4.3.3 An Incremental Debugging Strategy 191 3.4.4 Other Execution Slicing-Based Techniques in Software Fault Localization 193 3.5 Discussions 193 3.6 Conclusion 194 Notes 195 References 195 4 Spectrum-Based Techniques for Software Fault Localization 201 W. Eric Wong, Hua Jie Lee, Ruizhi Gao, and Lee Naish 4.1 Introduction 201 4.2 Background and Notation 203 4.2.1 Similarity Coefficient-Based Fault Localization 204 4.2.2 An Example of Using Similarity Coefficient to Compute Suspiciousness 205 4.3 Insights of Some Spectra-Based Metrics 210 4.4 Equivalence Metrics 212 4.4.1 Applicability of the Equivalence Relation to Other Fault Localization Techniques 217 4.4.2 Applicability Beyond Fault Localization 218 4.5 Selecting a Good Suspiciousness Function (Metric) 219 4.5.1 Cost of Using a Metric 219 4.5.2 Optimality for Programs with a Single Bug 220 4.5.3 Optimality for Programs with Deterministic Bugs 221 4.6 Using Spectrum-Based Metrics for Fault Localization 222 4.6.1 Spectrum-Based Metrics for Fault Localization 222 4.6.2 Refinement of Spectra-Based Metrics 227 4.7 Empirical Evaluation Studies of SBFL Metrics 232 4.7.1 The Construction of D ∗ 234 4.7.2 An Illustrative Example 235 4.7.3 A Case Study Using D ∗ 237 4.7.3.1 Subject Programs 237 4.7.3.2 Fault Localization Techniques Used in Comparisons 238 4.7.3.3 Evaluation Metrics and Criteria 239 4.7.3.4 Statement with Same Suspiciousness Values 240 4.7.3.5 Results 241 4.7.3.6 Effectiveness of D ∗ with Different Values of ∗ 247 4.7.3.7 D ∗ Versus Other Fault Localization Techniques 248 4.7.3.8 Programs with Multiple Bugs 251 4.7.3.9 Discussion 255 4.8 Conclusion 261 Notes 262 References 263 5 Statistics-Based Techniques for Software Fault Localization 271 Zhenyu Zhang and W. Eric Wong 5.1 Introduction 271 5.1.1 Tarantula 272 5.1.2 How It Works 272 5.2 Working with Statements 274 5.2.1 Techniques Under the Same Problem Settings 275 5.2.2 Statistical Variances 275 5.3 Working with Non-statements 283 5.3.1 Predicate: a Popular Trend 283 5.3.2 BPEL: a Sample Application 285 5.4 Purifying the Input 286 5.4.1 Coincidental Correctness Issue 286 5.4.2 Class Balance Consideration 287 5.5 Reinterpreting the Output 288 5.5.1 Revealing Fault Number 288 5.5.2 Noise Reduction 291 Notes 292 References 293 6 Machine Learning-Based Techniques for Software Fault Localization 297 W. Eric Wong 6.1 Introduction 297 6.2 BP Neural Network-Based Fault Localization 298 6.2.1 Fault Localization with a BP Neural Network 298 6.2.2 Reduce the Number of Candidate Suspicious Statements 302 6.3 RBF Neural Network-Based Fault Localization 304 6.3.1 RBF Neural Networks 304 6.3.2 Methodology 305 6.3.2.1 Fault Localization Using an RBF Neural Network 306 6.3.2.2 Training of the RBF Neural Network 307 6.3.2.3 Definition of a Weighted Bit-Comparison-Based Dissimilarity 309 6.4 C4.5 Decision Tree-Based Fault Localization 309 6.4.1 Category-Partition for Rule Induction 309 6.4.2 Rule Induction Algorithms 310 6.4.3 Statement Ranking Strategies 310 6.4.3.1 Revisiting Tarantula 310 6.4.3.2 Ranking Statements Based on C4.5 Rules 312 6.5 Applying Simulated Annealing with Statement Pruning for an SBFL Formula 314 6.6 Conclusion 317 Notes 317 References 317 7 Data Mining-Based Techniques for Software Fault Localization 321 Peggy Cellier, Mireille Ducassé, Sébastien Ferré, Olivier Ridoux, and W. Eric Wong 7.1 Introduction 321 7.2 Formal Concept Analysis and Association Rules 324 7.2.1 Formal Concept Analysis 325 7.2.2 Association Rules 327 7.3 Data Mining for Fault Localization 329 7.3.1 Failure Rules 329 7.3.2 Failure Lattice 331 7.4 The Failure Lattice for Multiple Faults 336 7.4.1 Dependencies Between Faults 336 7.4.2 Example 341 7.5 Discussion 342 7.5.1 The Structure of the Execution Traces 342 7.5.2 Union Model 343 7.5.3 Intersection Model 343 7.5.4 Nearest Neighbor 343 7.5.5 Delta Debugging 344 7.5.6 From the Trace Context to the Failure Context 344 7.5.7 The Structure of Association Rules 345 7.5.8 Multiple Faults 345 7.6 Fault Localization Using N-gram Analysis 346 7.6.1 Background 347 7.6.1.1 Execution Sequence 347 7.6.1.2 N-gram Analysis 347 7.6.1.3 Linear Execution Blocks 349 7.6.1.4 Association Rule Mining 349 7.6.2 Methodology 350 7.6.3 Conclusion 353 7.7 Fault Localization for GUI Software Using N-gram Analysis 353 7.7.1 Background 354 7.7.1.1 Representation of the GUI and Its Operations 354 7.7.1.2 Event Handler 356 7.7.1.3 N-gram 356 7.7.2 Association Rule Mining 357 7.7.3 Methodology 357 7.7.3.1 General Approach 358 7.7.3.2 N-gram Fault Localization Algorithm 358 7.8 Conclusion 360 Notes 361 References 361 8 Information Retrieval-Based Techniques for Software Fault Localization 365 Xin Xia and David Lo 8.1 Introduction 365 8.2 General IR-Based Fault Localization Process 368 8.3 Fundamental Information Retrieval Techniques for Software Fault Localization 369 8.3.1 Vector Space Model 369 8.3.2 Topic Modeling 370 8.3.3 Word Embedding 371 8.4 Evaluation Metrics 372 8.4.1 Top-k Prediction Accuracy 372 8.4.2 Mean Reciprocal Rank (MRR) 373 8.4.3 Mean Average Precision (MAP) 373 8.5 Techniques for Different Scenarios 374 8.5.1 Text of Current Bug Report Only 374 8.5.1.1 VSM Variants 374 8.5.1.2 Topic Modeling 375 8.5.2 Text and History 376 8.5.2.1 VSM Variants 376 8.5.2.2 Topic Modeling 378 8.5.2.3 Deep Learning 378 8.5.3 Text and Stack/Execution Traces 379 8.6 Empirical Studies 380 8.7 Miscellaneous 383 8.8 Conclusion 385 Notes 385 References 386 9 Model-Based Techniques for Software Fault Localization 393 Birgit Hofer, Franz Wotawa, Wolfgang Mayer, and Markus Stumptner 9.1 Introduction 393 9.2 Basic Definitions and Algorithms 395 9.2.1 Algorithms for MBD 401 9.3 Modeling for MBD 404 9.3.1 The Value-Based Model 405 9.3.2 The Dependency-Based Model 409 9.3.3 Approximation Models for Debugging 413 9.3.4 Other Modeling Approaches 416 9.4 Application Areas 417 9.5 Hybrid Approaches 418 9.6 Conclusions 419 Notes 420 References 420 10 Software Fault Localization in Spreadsheets 425 Birgit Hofer and Franz Wotawa 10.1 Motivation 425 10.2 Definition of the Spreadsheet Language 427 10.3 Cones 430 10.4 Spectrum-Based Fault Localization 431 10.5 Model-Based Spreadsheet Debugging 435 10.6 Repair Approaches 440 10.7 Checking Approaches 443 10.8 Testing 445 10.9 Conclusion 446 Notes 446 References 447 11 Theoretical Aspects of Software Fault Localization 451 Xiaoyuan Xie and W. Eric Wong 11.1 Introduction 451 11.2 A Model-Based Hybrid Analysis 452 11.2.1 The Model Program Segment 452 11.2.2 Important Findings 454 11.2.3 Discussion 454 11.3 A Set-Based Pure Theoretical Framework 455 11.3.1 Definitions and Theorems 455 11.3.2 Evaluation 457 11.3.3 The Maximality Among All Investigated Formulas 461 11.4 A Generalized Study 462 11.4.1 Spectral Coordinate for SBFL 462 11.4.2 Generalized Maximal and Greatest Formula in F 464 11.5 About the Assumptions 465 11.5.1 Omission Fault and 100% Coverage 465 11.5.2 Tie-Breaking Scheme 467 11.5.3 Multiple Faults 467 11.5.4 Some Plausible Causes for the Inconsistence Between Empirical and Theoretical Analyses 468 Notes 469 References 470 12 Software Fault Localization for Programs with Multiple Bugs 473 Ruizhi Gao, W. Eric Wong, and Rui Abreu 12.1 Introduction 473 12.2 One-Bug-at-a-Time 474 12.3 Two Techniques Proposed by Jones et al. 475 12.3.1 J1: Clustering Based on Profiles and Fault Localization Results 476 12.3.1.1 Clustering Profile-Based Behavior Models 476 12.3.1.2 Using Fault Localization to Stop Clustering 478 12.3.1.3 Using Fault Localization Clustering to Refine Clusters 479 12.3.2 J2: Clustering Based on Fault Localization Results 480 12.4 Localization of Multiple Bugs Using Algorithms from Integer Linear Programming 481 12.5 MSeer: an Advanced Fault Localization Technique for Locating Multiple Bugs in Parallel 483 12.5.1 MSeer 485 12.5.1.1 Representation of Failed Test Cases 485 12.5.1.2 Revised Kendall tau Distance 486 12.5.1.3 Clustering 488 12.5.1.4 MSeer: a Technique for Locating Multiple Bugs in Parallel 494 12.5.2 A Running Example 496 12.5.3 Case Studies 499 12.5.3.1 Subject Programs and Data Collections 499 12.5.3.2 Evaluation of Effectiveness and Efficiency 501 12.5.3.3 Results 503 12.5.4 Discussions 510 12.5.4.1 Using Different Fault Localization Techniques 510 12.5.4.2 Apply MSeer to Programs with a Single Bug 510 12.5.4.3 Distance Metrics 512 12.5.4.4 The Importance of Estimating the Number of Clusters and Assigning Initial Medoids 514 12.6 Spectrum-Based Reasoning for Fault Localization 514 12.6.1 Barinel 515 12.6.2 Results 517 12.7 Other Studies 518 12.8 Conclusion 520 Notes 521 References 522 13 Emerging Aspects of Software Fault Localization 529 T.H. Tse, David Lo, Alex Gorce, Michael Perscheid, Robert Hirschfeld, and W. Eric Wong 13.1 Introduction 529 13.2 Application of the Scientific Method to Fault Localization 530 13.2.1 Scientific Debugging 531 13.2.2 Identifying and Assigning Bug Reports to Developers 532 13.2.3 Using Debuggers in Fault Localization 534 13.2.4 Conclusion 538 13.3 Fault Localization in the Absence of Test Oracles by Semi-proving of Metamorphic Relations 538 13.3.1 Metamorphic Testing and Metamorphic Relations 539 13.3.2 The Semi-proving Methodology 541 13.3.2.1 Semi-proving by Symbolic Evaluation 541 13.3.2.2 Semi-proving as a Fault Localization Technique 542 13.3.3 The Need to Go Beyond Symbolic Evaluation 543 13.3.4 Initial Empirical Study 543 13.3.5 Detailed Illustrative Examples 544 13.3.5.1 Fault Localization Example Related to Predicate Statement 544 13.3.5.2 Fault Localization Example Related to Faulty Statement 548 13.3.5.3 Fault Localization Example Related to Missing Path 552 13.3.5.4 Fault Localization Example Related to Loop 556 13.3.6 Comparisons with Related Work 558 13.3.7 Conclusion 560 13.4 Automated Prediction of Fault Localization Effectiveness 560 13.4.1 Overview of PEFA 561 13.4.2 Model Learning 564 13.4.3 Effectiveness Prediction 564 13.4.4 Conclusion 564 13.5 Integrating Fault Localization into Automated Test Generation Tools 565 13.5.1 Localization in the Context of Automated Test Generation 566 13.5.2 Automated Test Generation Tools Supporting Localization 567 13.5.3 Antifragile Tests and Localization 568 13.5.4 Conclusion 568 Notes 569 References 569 Index 581

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Book SynopsisThe first comprehensive guide to the design and implementation of security in 5G wireless networks and devices Security models for 3G and 4G networks based on Universal SIM cards worked very well. But they are not fully applicable to the unique security requirements of 5G networks. 5G will face additional challenges due to increased user privacy concerns, new trust and service models and requirements to support IoT and mission-critical applications. While multiple books already exist on 5G, this is the first to focus exclusively on security for the emerging 5G ecosystem. 5G networks are not only expected to be faster, but provide a backbone for many new services, such as IoT and the Industrial Internet. Those services will provide connectivity for everything from autonomous cars and UAVs to remote health monitoring through body-attached sensors, smart logistics through item tracking to remote diagnostics and preventive maintenance of equipment. Most services will be integrated with Table of ContentsThe Editors xvii About the Contributors xxi Foreword xxxiii Preface xxxv Acknowledgements xli Part I 5G Security Overview 1 1 Evolution of Cellular Systems 3Shahriar Shahabuddin, Sadiqur Rahaman, Faisal Rehman, Ijaz Ahmad, and Zaheer Khan 1.1 Introduction 3 1.2 Early Development 4 1.3 First Generation Cellular Systems 6 1.3.1 Advanced Mobile Phone Service 7 1.3.2 Security in 1G 7 1.4 Second Generation Cellular Systems 8 1.4.1 Global System for Mobile Communications 8 1.4.2 GSM Network Architecture 9 1.4.3 Code Division Multiple Access 10 1.4.4 Security in 2G 10 1.4.5 Security in GSM 11 1.4.5.1 IMSI 11 1.4.5.2 Ki 12 1.4.5.3 A3 Algorithm 12 1.4.5.4 A8 Algorithm 13 1.4.5.5 COMP128 14 1.4.5.6 A5 Algorithm 14 1.4.6 Security in IS]95 14 1.5 Third Generation Cellular Systems 15 1.5.1 CDMA 2000 15 1.5.2 UMTS WCDMA 15 1.5.3 UMTS Network Architecture 16 1.5.4 HSPA 17 1.5.5 Security in 3G 17 1.5.6 Security in CDMA2000 17 1.5.7 Security in UMTS 18 1.6 Cellular Systems beyond 3G 20 1.6.1 HSPA+ 20 1.6.2 Mobile WiMAX 20 1.6.3 LTE 21 1.6.3.1 Orthogonal Frequency Division Multiplexing (OFDM) 21 1.6.3.2 SC]FDE and SC]FDMA 21 1.6.3.3 Multi]antenna Technique 21 1.6.4 LTE Network Architecture 21 1.7 Fourth Generation Cellular Systems 22 1.7.1 Key Technologies of 4G 23 1.7.1.1 Enhanced MINO 23 1.7.1.2 Cooperative Multipoint Transmission and Reception for LTE]Advanced 23 1.7.1.3 Spectrum and Bandwidth Management 24 1.7.1.4 Carrier Aggregation 24 1.7.1.5 Relays 24 1.7.2 Network Architecture 24 1.7.3 Beyond 3G and 4G Cellular Systems Security 25 1.7.4 LTE Security Model 26 1.7.5 Security in WiMAX 26 1.8 Conclusion 27 References 28 2 5G Mobile Networks: Requirements, Enabling Technologies, and Research Activities 31Van]Giang Nguyen, Anna Brunstrom, Karl]Johan Grinnemo, and Javid Taheri 2.1 Introduction 31 2.1.1 What is 5G? 31 2.1.1.1 From a System Architecture Perspective 32 2.1.1.2 From the Spectrum Perspective 32 2.1.1.3 From a User and Customer Perspective 32 2.1.2 Typical Use Cases 32 2.2 5G Requirements 33 2.2.1 High Data Rate and Ultra Low Latency 34 2.2.2 Massive Connectivity and Seamless Mobility 35 2.2.3 Reliability and High Availability 35 2.2.4 Flexibility and Programmability 36 2.2.5 Energy, Cost and Spectrum Efficiency 36 2.2.6 Security and Privacy 36 2.3 5G Enabling Technologies 37 2.3.1 5G Radio Access Network 38 2.3.1.1 mmWave Communication 38 2.3.1.2 Massive MIMO 38 2.3.1.3 Ultra]Dense Small Cells 39 2.3.1.4 M2M and D2D Communications 40 2.3.1.5 Cloud]based Radio Access Network 42 2.3.1.6 Mobile Edge and Fog Computing 42 2.3.2 5G Mobile Core Network 44 2.3.2.1 Software Defined Networking 44 2.3.2.2 Network Function Virtualization 44 2.3.2.3 Cloud Computing 46 2.3.3 G End]to]End System 46 2.3.3.1 Network Slicing 46 2.3.3.2 Management and Orchestration 47 2.4 5G Standardization Activities 48 2.4.1 ITU Activities 48 2.4.1.1 ITU]R 49 2.4.1.2 ITU]T 49 2.4.2 3GPP Activities 49 2.4.2.1 Pre]5G Phase 49 2.4.2.2 5G Phase I 50 2.4.2.3 5G Phase II 50 2.4.3 ETSI Activities 50 2.4.4 IEEE Activities 51 2.4.5 IETF Activities 52 2.5 5G Research Communities 52 2.5.1 European 5G Related Activities 52 2.5.1.1 5G Research in EU FP7 52 2.5.1.2 5G Research in EU H2020 52 2.5.1.3 5G Research in Celtic]Plus 53 2.5.2 Asian 5G Related Activities 53 2.5.2.1 South Korea: 5G Forum 53 2.5.2.2 Japan: 5GMF Forum 54 2.5.2.3 China: IMT]2020 5G Promotion Group 54 2.5.3 American 5G Related Activities 54 2.6 Conclusion 55 2.7 Acknowledgement 55 References 55 3 Mobile Networks Security Landscape 59Ahmed Bux Abro 3.1 Introduction 59 3.2 Mobile Networks Security Landscape 59 3.2.1 Security Threats and Protection for 1G 61 3.2.2 Security Threats and Protection for 2G 61 3.2.3 Security Threats and Protection for 3G 63 3.2.4 Security Threats and Protection for 4G 63 3.2.4.1 LTE UE (User Equipment) Domain Security 64 3.2.4.2 LTE (Remote Access Network) Domain Security 65 3.2.4.3 LTE Core Network Domain Security 65 3.2.4.4 Security Threat Analysis for 4G 65 3.2.5 Security Threats and Protection for 5G 66 3.2.5.1 Next Generation Threat Landscape for 5G 68 3.2.5.2 IoT Threat Landscape 68 3.2.5.3 5G Evolved Security Model 68 3.2.5.4 5G Security Threat Analysis 69 3.3 Mobile Security Lifecycle Functions 70 3.3.1 Secure Device Management 71 3.3.2 Mobile OS and App Patch Management 71 3.3.3 Security Threat Analysis and Assessment 71 3.3.4 Security Monitoring 72 3.4 Conclusion 73 References 73 4 Design Principles for 5G Security 75Ijaz Ahmad, Madhusanka Liyanage, Shahriar Shahabuddin, Mika Ylianttila, and Andrei Gurtov 4.1 Introduction 75 4.2 Overviews of Security Recommendations and Challenges 76 4.2.1 Security Recommendations by ITU]T 77 4.2.2 Security Threats and Recommendations by NGMN 78 4.2.3 Other Security Challenges 79 4.2.3.1 Security Challenges in the Access Network 79 4.2.3.2 DoS Attacks 79 4.2.3.3 Security Challenges in the Control Layer or Core Network 80 4.3 Novel Technologies for 5G Security 81 4.3.1 5G Security Leveraging NFV 82 4.3.2 Network Security Leveraging SDN 83 4.3.3 Security Challenges in SDN 84 4.3.3.1 Application Layer 84 4.3.3.2 Controller Layer 85 4.3.3.3 Infrastructure Layer 86 4.3.4 Security Solutions for SDN 86 4.3.4.1 Application Plane Security 86 4.3.4.2 Control Plane Security 87 4.3.4.3 Data Plane Security Solutions 87 4.4 Security in SDN]based Mobile Networks 88 4.4.1 Data Link Security 88 4.4.2 Control Channels Security 89 4.4.3 Traffic Monitoring 91 4.4.4 Access Control 91 4.4.5 Network Resilience 91 4.4.6 Security Systems and Firewalls 92 4.4.7 Network Security Automation 92 4.5 Conclusions and Future Directions 94 4.6 Acknowledgement 95 References 95 5 Cyber Security Business Models in 5G 99Julius Francis Gomes, Marika Iivari, Petri Ahokangas, Lauri Isotalo, Bengt Sahlin, and Jan Melén 5.1 Introduction 99 5.2 The Context of Cyber Security Businesses 100 5.2.1 Types of Cyber Threat 101 5.2.2 The Cost of Cyber]Attacks 102 5.3 The Business Model Approach 103 5.3.1 The 4C Typology of the ICT Business Model 104 5.3.2 Business Models in the Context of Cyber Preparedness 105 5.4 The Business Case of Cyber Security in the Era of 5G 106 5.4.1 The Users and Issues of Cyber Security in 5G 108 5.4.2 Scenarios for 5G Security Provisioning 109 5.4.3 Delivering Cyber Security in 5G 110 5.5 Business Model Options in 5G Cyber Security 112 5.6 Acknowledgment 114 References 114 Part II 5G Network Security 117 6 Physical Layer Security 119Simone Soderi, Lorenzo Mucchi, Matti Hämäläinen, Alessandro Piva, and Jari Iinatti 6.1 Introduction 119 6.1.1 Physical Layer Security in 5G Networks 120 6.1.2 Related Work 121 6.1.3 Motivation 121 6.2 WBPLSec System Model 123 6.2.1 Transmitter 124 6.2.2 Jamming Receiver 126 6.2.3 Secrecy Metrics 126 6.2.4 Secrecy Capacity of WBPLSec 128 6.2.5 Secrecy Capacity of iJAM 129 6.3 Outage Probability of Secrecy Capacity of a Jamming Receiver 131 6.3.1 Simulation Scenario for Secrecy Capacity 134 6.4 WBPLSec Applied to 5G networks 136 6.5 Conclusions 138 References 139 7 5G]WLAN Security 143Satish Anamalamudi, Abdur Rashid Sangi, Mohammed Alkatheiri, Fahad T. Bin Muhaya, and Chang Liu 7.1 Chapter Overview 143 7.2 Introduction to WiFi]5G Networks Interoperability 143 7.2.1 WiFi (Wireless Local Area Network) 143 7.2.2 Interoperability of WiFi with 5G Networks 144 7.2.3 WiFi Security 144 7.3 Overview of Network Architecture for WiFi]5G Networks Interoperability 146 7.3.1 MAC Layer 147 7.3.2 Network Layer 147 7.3.3 Transport Layer 148 7.3.4 Application Layer 149 7.4 5G]WiFi Security Challenges 150 7.4.1 Security Challenges with Respect to a Large Number of Device Connectivity 151 7.4.2 Security Challenges in 5G Networks and WiFi 151 7.5 Security Consideration for Architectural Design of WiFi]5G Networks 156 7.5.1 User and Device Identity Confidentiality 156 7.5.2 Integrity 156 7.5.3 Mutual Authentication and Key Management 157 7.6 LiFi Networks 158 7.7 Introduction to LiFi]5G Networks Interoperability 159 7.8 5G]LiFi Security Challenges 160 7.8.1 Security Challenges with Respect to a Large Number of Device Connectivity 160 7.8.2 Security Challenges in 5G Networks and LiFi 160 7.9 Security Consideration for Architectural Design of LiFi]5G Networks 160 7.10 Conclusion and Future Work 161 References 161 8 Safety of 5G Network Physical Infrastructures 165Rui Travanca and João André 8.1 Introduction 165 8.2 Historical Development 168 8.2.1 Typology 168 8.2.2 Codes 170 8.2.3 Outlook 170 8.3 Structural Design Philosophy 171 8.3.1 Basis 171 8.3.2 Actions 174 8.3.3 Structural Analysis 179 8.3.4 Steel Design Verifications 180 8.3.4.1 Ultimate Limit States 180 8.3.4.2 Serviceability Limit States 181 8.4 Survey of Problems 181 8.4.1 General 181 8.4.2 Design Failures 182 8.4.3 Maintenance Failures 183 8.4.4 Vandalism or Terrorism Failures 186 8.5 Opportunities and Recommendations 188 8.6 Acknowledgement 190 References 191 9 Customer Edge Switching: A Security Framework for 5G 195Hammad Kabir, Raimo Kantola, and Jesus Llorente Santos 9.1 Introduction 195 9.2 State]of]the]art in Mobile Networks Security 197 9.2.1 Mobile Network Challenges and Principles of Security Framework 200 9.2.2 Trust Domains and Trust Processing 202 9.3 CES Security Framework 203 9.3.1 DNS to Initiate Communication 205 9.3.2 CETP Policy]based Communication 206 9.3.3 Policy Architecture 208 9.3.4 CES Security Mechanisms 209 9.3.5 Realm Gateway 210 9.3.6 RGW Security Mechanisms 211 9.3.6.1 Name Server Classification and Allocation Model 212 9.3.6.2 Preventing DNS Abuse 212 9.3.6.3 Bot]Detection Algorithm 213 9.3.6.4 TCP]Splice 213 9.4 Evaluation of CES Security 213 9.4.1 Evaluating the CETP Policy]based Communication 214 9.4.1.1 Security Testing 216 9.4.1.2 Outcomes of the Security Testing 216 9.4.2 Evaluation of RGW Security 217 9.5 Deployment in 5G Networks 222 9.5.1 Use Case 1: Mobile Broadband 224 9.5.1.1 Deployment and Operations 224 9.5.1.2 Security Benefits 224 9.5.1.3 Scalability 225 9.5.1.4 Reliability 225 9.5.2 Use Case 2: Corporate Gateway 225 9.5.2.1 Deployment and Operations 225 9.5.2.2 Security Benefits 226 9.5.2.3 Scalability 226 9.5.2.4 Reliability 226 9.5.3 Use Case 3: National CERT Centric Trust Domain 226 9.5.3.1 Deployment and Operations 226 9.5.3.2 Security Benefits 227 9.5.3.3 Scalability 227 9.5.3.4 Reliability 227 9.5.4 Use Case 4: Industrial Internet for Road Traffic and Transport 227 9.5.4.1 Deployment and Operations 227 9.5.4.2 Security Benefits 228 9.5.4.3 Scalability 228 9.5.4.4 Reliability 228 9.6 Conclusion 228 References 230 10 Software Defined Security Monitoring in 5G Networks 231Madhusanka Liyanage, Ijaz Ahmad, Jude Okwuibe, Edgardo Montes de Oca, Mai Hoang Long, Oscar Lopez Perez, and Mikel Uriarte Itzazelaia 10.1 Introduction 231 10.2 Existing Monitoring Techniques 232 10.3 Limitations on Current Monitoring Techniques 233 10.4 Use of Monitoring in 5G 234 10.5 Software]Defined Monitoring Architecture 235 10.6 Expected Advantages of Software Defined Monitoring 238 10.7 Expected Challenges in Software Defined Monitoring 240 10.8 Conclusion 242 References 243 Part III 5G Device and User Security 245 11 IoT Security 247Mehrnoosh Monshizadeh, and Vikramajeet Khatri 11.1 Introduction 247 11.2 Related Work 248 11.3 Literature Overview and Research Motivation 249 11.3.1 IoT Devices, Services and Attacks on Them 250 11.3.2 Research Motivation 253 11.4 Distributed Security Platform 254 11.4.1 Robot Data Classification 254 11.4.2 Robot Attack Classification 255 11.4.3 Robot Security Platform 256 11.4.3.1 Robot Section 257 11.4.3.2 Mobile Network Section 257 11.5 Mobile Cloud Robot Security Scenarios 259 11.5.1 Robot with SIMcard 259 11.5.2 SIMless Robot 260 11.5.3 Robot Attack 263 11.5.4 Robot Communication 263 11.6 Conclusion 263 References 265 12 User Privacy, Identity and Trust 267Tanesh Kumar, Madhusanka Liyanage, Ijaz Ahmad, An Braeken, and Mika Ylianttila 12.1 Introduction 267 12.2 Background 268 12.3 User Privacy 269 12.3.1 Data Privacy 269 12.3.2 Location Privacy 271 12.3.3 Identity Privacy 272 12.4 Identity Management 273 12.5 Trust Models 274 12.6 Discussion 277 12.7 Conclusion 278 References 279 13 5G Positioning: Security and Privacy Aspects 281Elena Simona Lohan, Anette Alén]Savikko, Liang Chen, Kimmo Järvinen, Helena Leppäkoski, Heidi Kuusniemi, and Päivi Korpisaari 13.1 Introduction 281 13.2 Outdoor versus Indoor Positioning Technologies 283 13.3 Passive versus Active Positioning 283 13.4 Brief Overview of 5G Positioning Mechanisms 285 13.5 Survey of Security Threats and Privacy Issues in 5G Positioning 291 13.5.1 Security Threats in 5G Positioning 291 13.5.1.1 Security Threats Affecting Several or All Players 291 13.5.1.2 Security Threats Affecting LISP 292 13.5.1.3 Security Threats Affecting LBSP 293 13.5.1.4 Security Threats Affecting the 5G User Device or LIC 293 13.6 Main Privacy Concerns 294 13.7 Passive versus Active Positioning Concepts 295 13.8 Physical] Layer Based Security Enhancements Mechanisms for Positioning in 5G 296 13.8.1 Reliability Monitoring and Outlier Detection Mechanisms 296 13.8.2 Detection, Location and Estimation of Interference Signals 297 13.8.3 Backup Systems 298 13.9 Enhancing Trustworthiness 299 13.10 Cryptographic Techniques for Security and Privacy of Positioning 299 13.10.1 Cryptographic Authentication in Positioning 300 13.10.2 Cryptographic Distance]Bounding 301 13.10.3 Cryptographic Techniques for Privacy]Preserving Location]based Services 303 13.11 Legislation on User Location Privacy in 5G 304 13.11.1 EU Policy and Legal Framework 304 13.11.2 Legal Aspects Related to the Processing of Location Data 306 13.11.3 Privacy Protection by Design and Default 306 13.11.4 Security Protection 307 13.11.5 A Closer Look at the e]Privacy Directive 307 13.11.6 Summary of EU Legal Instruments 308 13.11.7 International Issues 308 13.11.8 Challenges and Future Scenarios in Legal Frameworks and Policy 309 13.12 Landscape of the European and International Projects related to Secure Positioning 311 References 312 Part IV 5G Cloud and Virtual Network Security 321 14 Mobile Virtual Network Operators (MVNO) Security 323Mehrnoosh Monshizadeh and Vikramajeet Khatri 14.1 Introduction 323 14.2 Related Work 324 14.3 Cloudification of the Network Operators 325 14.4 MVNO Security 326 14.4.1 Data Security in TaaS 327 14.4.2 Hypervisor and VM Security in TaaS 328 14.4.2.1 SDN Security in TaaS 329 14.4.2.2 NFV Security in TaaS 331 14.4.2.3 OPNFV Security 332 14.4.3 Application Security in TaaS 333 14.4.4 Summary 334 14.4.5 MVNO Security Benchmark 335 14.5 TaaS Deployment Security 338 14.5.1 IaaS 338 14.5.2 PaaS 340 14.5.3 SaaS 340 14.6 Future Directions 340 14.7 Conclusion 341 References 342 15 NFV and NFV]based Security Services 347Wenjing Chu 15.1 Introduction 347 15.2 5G, NFV and Security 347 15.3 A Brief Introduction to NFV 348 15.4 NFV, SDN, and a Telco Cloud 351 15.5 Common NFV Drivers 353 15.5.1 Technology Curve 353 15.5.2 Opportunity Cost and Competitive Landscape 353 15.5.3 Horizontal Network Slicing 354 15.5.4 Multi]Tenancy 354 15.5.5 Rapid Service Delivery 354 15.5.6 XaaS Models 354 15.5.7 One Cloud 355 15.6 NFV Security: Challenges and Opportunities 355 15.6.1 VNF Security Lifecycle and Trust 355 15.6.2 VNF Security in Operation 358 15.6.3 Multi]Tenancy and XaaS 359 15.6.4 OPNFV and Openstack: Open Source Projects for NFV 360 15.7 NFV]based Security Services 364 15.7.1 NFV]based Network Security 365 15.7.1.1 Virtual Security Appliances 365 15.7.1.2 Distributed Network Security Services 366 15.7.1.3 Network Security as a Service 366 15.7.2 Policy]based Security Services 366 15.7.2.1 Group]based Policy 367 15.7.2.2 Openstack Congress 368 15.7.3 Machine Learning for NFV]based Security Services 369 15.8 Conclusions 370 References 370 16 Cloud and MEC Security 373Jude Okwuibe, Madhusanka Liyanage, Ijaz Ahmed, and Mika Ylianttila 16.1 Introduction 373 16.2 Cloud Computing in 5G Networks 374 16.2.1 Overview and History of Cloud Computing 375 16.2.2 Cloud Computing Architecture 376 16.2.3 Cloud Deployment Models 377 16.2.4 Cloud Service Models 378 16.2.5 5G Cloud Computing Architecture 379 16.2.6 Use Cases/Scenarios of Cloud Computing in 5G 380 16.3 MEC in 5G Networks 381 16.3.1 Overview of MEC Computing 381 16.3.2 MEC in 5G 383 16.3.3 Use Cases of MEC Computing in 5G 384 16.4 Security Challenges in 5G Cloud 385 16.4.1 Virtualization Security 385 16.4.2 Cyber]Physical System (CPS) Security 386 16.4.3 Secure and Private Data Computation 386 16.4.4 Cloud Intrusion 387 16.4.5 Access Control 387 16.5 Security Challenges in 5G MEC 388 16.5.1 Denial of Service (DoS) Attack 389 16.5.2 Man]in]the]Middle (MitM) 389 16.5.3 Inconsistent Security Policies 389 16.5.4 VM Manipulation 390 16.5.5 Privacy Leakage 390 16.6 Security Architectures for 5G Cloud and MEC 391 16.6.1 Centralized Security Architectures 391 16.6.2 SDN]based Cloud Security Systems 392 16.7 5GMEC, Cloud Security Research and Standardizations 392 16.8 Conclusions 394 References 394 17 Regulatory Impact on 5G Security and Privacy 399Jukka Salo and Madhusanka Liyanage 17.1 Introduction 399 17.2 Regulatory Objectives for Security and Privacy 401 17.2.1 Generic Objectives 401 17.3 Legal Framework for Security and Privacy 402 17.3.1 General Framework 402 17.3.2 Legal Framework for Security and Privacy in Cloud Computing 403 17.3.3 Legal Framework for Security and Privacy in Software Defined Networking and Network Function Virtualization 405 17.4 Security and Privacy Issues in New 5G Technologies 405 17.4.1 Security and Privacy Issues in Cloud Computing 405 17.4.2 Security and Privacy Issues in Network Functions Virtualization 407 17.4.3 Security and Privacy Issues in Software Defined Networking (SDN) 409 17.4.4 Summary of Security and Privacy Issues in the Context of Technologies under Study (Clouds, NFV, SDN) 410 17.5 Relevance Assessment of Security and Privacy Issues for Regulation 411 17.6 Analysis of Potential Regulatory Approaches 412 17.7 Summary of Issues and Impact of New Technologies on Security and Privacy Regulation 413 References 417 Index

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Book SynopsisA guide to lithium sulfur batteries that explores their materials, electrochemical mechanisms and modelling and includes recent scientific developments Lithium Sulfur Batteries (Li-S) offers a comprehensive examination of Li-S batteries from the viewpoint of the materials used in their construction, the underlying electrochemical mechanisms and how this translates into the characteristics of Li-S batteries. The authors noted experts in the field outline the approaches and techniques required to model Li-S batteries. Lithium Sulfur Batteries reviews the application of Li-S batteries for commercial use and explores many broader issues including the development of battery management systems to control the unique characteristics of Li-S batteries. The authors include information onsulfur cathodes, electrolytes and other components used in making Li-S batteries and examine the role of lithium sulfide, the shuttle mechanism and its effects, and degradaTable of ContentsPreface xiii Part I Materials 1 1 Electrochemical Theory and Physics 3Geraint Minton 1.1 Overview of a LiS cell 3 1.2 The Development of the Cell Voltage 5 1.2.1 Using the Electrochemical Potential 7 1.2.2 Electrochemical Reactions 10 1.2.3 The Electric Double Layer 13 1.2.4 Reaction Equilibrium 15 1.2.5 A Finite Electrolyte 17 1.2.6 The Need for a Second Electrode 17 1.3 Allowing a Current to Flow 19 1.3.1 The Reaction Overpotential 20 1.3.2 The Transport Overpotential 21 1.3.3 General Comments on the Overpotentials 22 1.4 Additional Processes Which Define the Behavior of a LiS Cell 22 1.4.1 Multiple Electrochemical Reactions at One Surface 22 1.4.2 Chemical Reactions 23 1.4.3 Species Solubility and Indirect Reaction Effects 25 1.4.4 Transport Limitations in the Cathode 25 1.4.5 The Active Surface Area 26 1.4.6 Precipitate Accumulation 27 1.4.7 Electrolyte Viscosity, Conductivity, and Species Transport 27 1.4.8 Side Reactions and SEI Formation at the Anode 28 1.4.9 Anode Morphological Changes 29 1.4.10 Polysulfide Shuttle 29 1.5 Summary 30 References 30 2 Sulfur Cathodes 33Holger Althues, Susanne Dörfler, Sören Thieme, Patrick Strubel and Stefan Kaskel 2.1 Cathode Design Criteria 33 2.1.1 Overview of Cathode Components and Composition 33 2.1.2 Cathode Design: Role of Electrolyte in Sulfur Cathode Chemistry 34 2.1.3 Cathode Design: Impact on Energy Density on Cell Level 35 2.1.4 Cathode Design: Impact on Cycle Life and Self-discharge 36 2.1.5 Cathode Design: Impact on Rate Capability 37 2.2 Cathode Materials 37 2.2.1 Properties of Sulfur 37 2.2.2 Porous and Nanostructured Carbons as Conductive Cathode Scaffolds 39 2.2.2.1 Graphite-Like Carbons 39 2.2.2.2 Synthesis of Graphite-like Carbons 39 2.2.2.3 Carbon Black 40 2.2.2.4 Activated Carbons 41 2.2.2.5 Carbide-Derived Carbon 42 2.2.2.6 Hard-Template-Assisted Carbon Synthesis 42 2.2.2.7 Carbon Surface Chemistry 43 2.2.3 Carbon/Sulfur Composite Cathodes 43 2.2.3.1 Microporous Carbons 44 2.2.3.2 Mesoporous Carbons 45 2.2.3.3 Macroporous Carbons and Nanotube–based Cathode Systems 46 2.2.3.4 Hierarchical Mesoporous Carbons 47 2.2.3.5 Hierarchical Microporous Carbons 49 2.2.3.6 Hollow Carbon Spheres 50 2.2.3.7 Graphene 51 2.2.4 Retention of LiPS by Surface Modifications and Coating 51 2.2.4.1 Metal Oxides as Adsorbents for Lithium Polysulfides 56 2.3 Cathode Processing 57 2.3.1 Methods for C/S Composite Preparation 57 2.3.2 Wet (Organic, Aqueous) and Dry Coating for Cathode Production 58 2.3.3 Alternative Cathode Support Concepts (Carbon Current Collectors, Binder-free Electrodes) 59 2.3.4 Processing Perspective for Carbons, Binders, and Additives 59 2.4 Conclusions 59 References 61 3 Electrolyte for Lithium–Sulfur Batteries 71Marzieh Barghamadi, Mustafa Musameh, Thomas Rüther, Anand I. Bhatt, Anthony F. Hollenkamp and Adam S. Best 3.1 The Case for Better Batteries 71 3.2 Li–S Battery: Origins and Principles 72 3.3 Solubility of Species and Electrochemistry 74 3.4 Liquid Electrolyte Solutions 75 3.5 Modified Liquid Electrolyte Solutions 91 3.5.1 Variation in Electrolyte Salt Concentration 91 3.5.2 Mixed Organic–Ionic Liquid Electrolyte Solutions 91 3.5.3 Ionic Liquid Electrolyte Solutions 93 3.6 Solid and Solidified Electrolyte Configurations 96 3.6.1 Polymer Electrolytes 96 3.6.1.1 Absorbed Liquid/Gelled Electrolyte 96 3.6.1.2 Solid Polymer Electrolytes 98 3.6.2 Non-polymer Solid Electrolytes 100 3.7 Challenges of the Cathode and Solvent for Device Engineering 102 3.7.1 The Cathode Loading Challenge 102 3.7.2 Cathode Wetting Challenge 104 3.8 Concluding Remarks and Outlook 108 References 111 4 Anode–Electrolyte Interface 121Mark Wild 4.1 Introduction 121 4.2 SEI Formation 121 4.3 Anode Morphology 122 4.4 Polysulfide Shuttle 123 4.5 Electrolyte Additives for Stable SEI Formation 123 4.6 Barrier Layers on the Anode 125 4.7 A Systemic Approach 126 References 126 Part II Mechanisms 129 Reference 131 5 Molecular Level Understanding of the Interactions Between Reaction Intermediates of Li–S Energy Storage Systems and Ether Solvents 133Rajeev S. Assary and Larry A. Curtiss 5.1 Introduction 133 5.2 Computational Details 135 5.3 Results and Discussions 135 5.3.1 Reactivity of Li–S Intermediates with Dimethoxy Ethane (DME) 136 5.3.2 Kinetic Stability of Ethers in the Presence of Lithium Polysulfide 138 5.3.3 Linear Fluorinated Ethers 140 5.4 Summary and Conclusions 144 Acknowledgments 144 References 144 6 Lithium Sulfide 147Sylwia Walu´s 6.1 Introduction 147 6.2 Li2S as the End Discharge Product 148 6.2.1 General 148 6.2.2 Discharge Product: Li2S or Li2S2/Li2S? 151 6.2.3 A Survey of Experimental andTheoretical Findings Involving Li2S and Li2S2 Formation and Proposed Reduction Pathways 153 6.2.4 Mechanistic Insight into Li2S/Li2S2 Nucleation and Growth 157 6.2.5 Strategies to Limit Li2S Precipitation and Enhance the Capacity 160 6.2.6 Charge Mechanism and its Difficulties 161 6.3 Li2S-Based Cathodes: Toward a Li Ion System 164 6.3.1 General 164 6.3.2 Initial Activation of Li2S – Mechanism of First Charge 165 6.3.3 Recent Developments in Li2S Cathodes for Improved Performances 171 6.4 Summary 176 References 176 7 Degradation in Lithium–Sulfur Batteries 185Rajlakshmi Purkayastha 7.1 Introduction 185 7.2 Degradation Processes Within a Lithium–Sulfur Cell 190 7.2.1 Degradation at Cathode 190 7.2.2 Degradation at Anode 194 7.2.3 Degradation in Electrolyte 197 7.2.4 Degradation Due to Operating Conditions: Temperature, C-Rates, and Pressure 200 7.2.5 Degradation Due to Geometry: Scale-Up and Topology 205 7.3 Capacity Fade Models 209 7.3.1 Dendrite Models 211 7.3.2 Equivalent Circuit Network Models 213 7.4 Methods of Detecting and Measuring Degradation 214 7.4.1 Incremental Capacity Analysis 215 7.4.2 Differential Thermal Voltammetry 215 7.4.3 Electrochemical Impedance Spectroscopy 215 7.4.4 Resistance Curves 216 7.4.5 Macroscopic Indicators 217 7.5 Methods for Countering Degradation 218 7.6 Future Direction 221 References 222 Part III Modeling 227 8 Lithium–Sulfur Model Development 229Teng Zhang, Monica Marinescu and Gregory J. Offer 8.1 Introduction 229 8.2 Zero-Dimensional Model 231 8.2.1 Model Formulation 231 8.2.1.1 Electrochemical Reactions 231 8.2.1.2 Shuttle and Precipitation 232 8.2.1.3 Time Evolution of Species 233 8.2.1.4 Model Implementation 233 8.2.2 Basic Charge/Discharge Behaviors 233 8.3 Modeling Voltage Loss in Li–S Cells 236 8.3.1 Electrolyte Resistance 237 8.3.2 Anode Potential 238 8.3.3 Surface Passivation 239 8.3.4 Transport Limitation 240 8.4 Higher Dimensional Models 242 8.4.1 One-Dimensional Models 242 8.4.2 Multi-Scale Models 244 8.5 Summary 245 References 246 9 Battery Management Systems – State Estimation for Lithium–Sulfur Batteries 249Daniel J. Auger, Abbas Fotouhi, Karsten Propp and Stefano Longo 9.1 Motivation 249 9.1.1 Capacity 249 9.1.2 State of Charge (SoC) 251 9.1.3 State of Health (SoH) 251 9.1.4 Limitations of Existing Battery State Estimation Techniques 252 9.1.4.1 SoC Estimation from “Coulomb Counting” 252 9.1.4.2 SoC Estimation from Open-Circuit Voltage (OCV) 253 9.1.5 Direction of Current Work 253 9.2 Experimental Environment for Li–S Algorithm Development 254 9.2.1 Pulse Discharge Tests 255 9.2.2 Driving Cycle Tests 255 9.3 State Estimation Techniques from Control Theory 256 9.3.1 Electrochemical Models 257 9.3.2 Equivalent Circuit Network (ECN) Models 258 9.3.3 Kalman Filters and Their Derivatives 259 9.4 State Estimation Techniques from Computer Science 261 9.4.1 ANFIS as a Modeling Tool 261 9.4.2 Human Knowledge and Fuzzy Inference Systems (FIS) 263 9.4.3 Adaptive Neuro-Fuzzy Inference Systems 266 9.4.4 State-of-Charge Estimation Using ANFIS 268 9.5 Conclusions and Further Directions 269 Acknowledgments 270 References 270 Part IV Application 273 10 Commercial Markets for Li–S 275Mark Crittenden 10.1 Technology Strengths Meet Market Needs 275 10.1.1 Weight 275 10.1.2 Safety 276 10.1.3 Cost 276 10.1.4 Temperature Tolerance 276 10.1.5 Shipment and Storage 277 10.1.6 Power Characteristics 277 10.1.7 Environmentally Friendly Technology (Clean Tech) 278 10.1.8 Pressure Tolerance 278 10.1.9 Control 278 10.2 Electric Aircraft 278 10.3 Satellites 280 10.4 Cars 280 10.5 Buses 282 10.6 Trucks 283 10.7 Electric Scooter and Electric Bikes 284 10.8 Marine 285 10.9 Energy Storage 285 10.10 Low-Temperature Applications 286 10.11 Defense 286 10.12 Looking Ahead 286 10.13 Conclusion 287 11 Battery Engineering 289Gregory J. Offer 11.1 Mechanical Considerations 289 11.2 Thermal and Electrical Considerations 289 References 292 12 Case Study 293Paul Brooks 12.1 Introduction 293 12.2 A Potted History of Eternal Solar Flight 293 12.3 Why Has It Been So Difficult? 295 12.4 Objectives of HALE UAV 297 12.4.1 Stay Above the Cloud 298 12.4.2 Stay Above the Wind 298 12.4.3 Stay in the Sun 299 12.4.4 Year-Round Markets 300 12.4.5 Seasonal Markets 303 12.4.6 How Valuable Are These Markets and What Does That Mean for the Battery? 303 12.5 Worked Example – HALE UAV 303 12.6 Cells, Batteries, and Real Life 305 12.6.1 Cycle Life, Charge, and Discharge Rates 305 12.6.2 Payload 306 12.6.3 Avionics 306 12.6.4 Temperature 306 12.6.5 End-of-Life Performance 306 12.6.6 Protection 306 12.6.7 Balancing – Useful Capacity 307 12.6.8 Summary of Real-World Issues 307 12.7 A Quick Aside on Regenerative Fuel Cells 308 12.8 So What Do We Need from Our Battery Suppliers? 309 12.9 The Challenges for Battery Developers 310 12.10 The Answer to the Title 310 12.11 Summary 310 Acknowledgments 311 References 311 Index 313

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Book SynopsisA new approach to the issue of data quality in pattern recognition Detailing foundational concepts before introducing more complex methodologies and algorithms, this book is a self-contained manual for advanced data analysis and data mining. Top-down organization presents detailed applications only after methodological issues have been mastered, and step-by-step instructions help ensure successful implementation of new processes. By positioning data quality as a factor to be dealt with rather than overcome, the framework provided serves as a valuable, versatile tool in the analysis arsenal. For decades, practical need has inspired intense theoretical and applied research into pattern recognition for numerous and diverse applications. Throughout, the limiting factor and perpetual problem has been dataits sheer diversity, abundance, and variable quality presents the central challenge to pattern recognition innovation. Pattern Recognition: A Quality of Data PersTable of ContentsPREFACE ix PART 1 FUNDAMENTALS 1 CHAPTER 1 PATTERN RECOGNITION: FEATURE SPACE CONSTRUCTION 3 1.1 Concepts 3 1.2 From Patterns to Features 8 1.3 Features Scaling 17 1.4 Evaluation and Selection of Features 23 1.5 Conclusions 47 Appendix 1.A 48 Appendix 1.B 50 References 50 CHAPTER 2 PATTERN RECOGNITION: CLASSIFIERS 53 2.1 Concepts 53 2.2 Nearest Neighbors Classification Method 55 2.3 Support Vector Machines Classification Algorithm 57 2.4 Decision Trees in Classification Problems 65 2.5 Ensemble Classifiers 78 2.6 Bayes Classifiers 82 2.7 Conclusions 97 References 97 CHAPTER 3 CLASSIFICATION WITH REJECTION PROBLEM FORMULATION AND AN OVERVIEW 101 3.1 Concepts 102 3.2 The Concept of Rejecting Architectures 107 3.3 Native Patterns-Based Rejection 112 3.4 Rejection Option in the Dataset of Native Patterns: A Case Study 118 3.5 Conclusions 129 References 130 CHAPTER 4 EVALUATING PATTERN RECOGNITION PROBLEM 133 4.1 Evaluating Recognition with Rejection: Basic Concepts 133 4.2 Classification with Rejection with No Foreign Patterns 145 4.3 Classification with Rejection: Local Characterization 149 4.4 Conclusions 156 References 156 CHAPTER 5 RECOGNITION WITH REJECTION: EMPIRICAL ANALYSIS 159 5.1 Experimental Results 160 5.2 Geometrical Approach 175 5.3 Conclusions 191 References 192 PART 2 ADVANCED TOPICS: A FRAMEWORK OF GRANULAR COMPUTING 195 CHAPTER 6 CONCEPTS AND NOTIONS OF INFORMATION GRANULES 197 6.1 Information Granularity and Granular Computing 197 6.2 Formal Platforms of Information Granularity 201 6.3 Intervals and Calculus of Intervals 205 6.4 Calculus of Fuzzy Sets 208 6.5 Characterization of Information Granules: Coverage and Specificity 216 6.6 Matching Information Granules 219 6.7 Conclusions 220 References 221 CHAPTER 7 INFORMATION GRANULES: FUNDAMENTAL CONSTRUCTS 223 7.1 The Principle of Justifiable Granularity 223 7.2 Information Granularity as a Design Asset 230 7.3 Single-Step and Multistep Prediction of Temporal Data in Time Series Models 235 7.4 Development of Granular Models of Higher Type 236 7.5 Classification with Granular Patterns 241 7.6 Conclusions 245 References 246 CHAPTER 8 CLUSTERING 247 8.1 Fuzzy C-Means Clustering Method 247 8.2 k-Means Clustering Algorithm 252 8.3 Augmented Fuzzy Clustering with Clusters and Variables Weighting 253 8.4 Knowledge-Based Clustering 254 8.5 Quality of Clustering Results 254 8.6 Information Granules and Interpretation of Clustering Results 256 8.7 Hierarchical Clustering 258 8.8 Information Granules in Privacy Problem: A Concept of Microaggregation 261 8.9 Development of Information Granules of Higher Type 262 8.10 Experimental Studies 264 8.11 Conclusions 272 References 273 CHAPTER 9 QUALITY OF DATA: IMPUTATION AND DATA BALANCING 275 9.1 Data Imputation: Underlying Concepts and Key Problems 275 9.2 Selected Categories of Imputation Methods 276 9.3 Imputation with the Use of Information Granules 278 9.4 Granular Imputation with the Principle of Justifiable Granularity 279 9.5 Granular Imputation with Fuzzy Clustering 283 9.6 Data Imputation in System Modeling 285 9.7 Imbalanced Data and their Granular Characterization 286 9.8 Conclusions 291 References 291 INDEX 293

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Book SynopsisA systematic view of hierarchical protection for smart grids, with solutions to tradition protection problems and complicated operation modes of modern power systems Systematically investigates traditional protection problems from the bird's eye view of hierarchical protection Focuses on multiple variable network structures and complicated operation modes Offers comprehensive countermeasures on improving protection performance based on up-to-date researchTable of ContentsAbout the Author ix Foreword xi Preface xiii Introduction xv 1 Basic Theories of Power System Relay Protection 1 1.1 Introduction 1 1.2 Function of Relay Protection 1 1.3 Basic Requirements of Relay Protection 3 1.3.1 Reliability 3 1.3.2 Selectivity 4 1.3.3 Speed 4 1.3.4 Sensitivity 5 1.4 Basic Principles of Relay Protection 6 1.4.1 Over-Current Protection 6 1.4.2 Directional Current Protection 6 1.4.3 Distance Protection 7 1.5 Hierarchical Relay Protection 9 1.5.1 Local Area Protection 10 1.5.2 Substation Area Protection 11 1.5.3 Wide Area Protection 12 1.5.4 Constitution Mode of Hierarchical Relay Protection 13 1.6 Summary 15 References 15 2 Local Area Conventional Protection 17 2.1 Introduction 17 2.2 Transformer Protection 18 2.2.1 Adaptive Scheme of Discrimination between Internal Faults and Inrush Currents of Transformer Using Mathematical Morphology 18 2.2.2 Algorithm to Discriminate Internal Fault Current and Inrush Current Utilizing Variation Feature of Fundamental Current Amplitude 30 2.2.3 Identifying Transformer Inrush Current Based on Normalized Grille Curve (NGC) 39 2.2.4 Adaptive Method to Identify CT Saturation Using Grille Fractal 50 2.2.5 Algorithm for Discrimination Between Inrush Currents and Internal Faults Based on Equivalent Instantaneous Leakage Inductance 57 2.2.6 A Two-Terminal Network-Based Method for Discrimination between Internal Faults and Inrush Currents 70 2.3 Transmission Line Protection 82 2.3.1 Line Protection Scheme for Single-Phase-to-Ground Faults Based on Voltage Phase Comparison 83 2.3.2 Adaptive Distance Protection Scheme Based on the Voltage Drop Equation 99 2.3.3 Location Method for Inter-Line and Grounded Faults of Double-Circuit Transmission Lines Based on Distributed Parameters 117 2.3.4 Adaptive Overload Identification Method Based on Complex Phasor Plane 134 2.3.5 Novel Fault Phase Selection Scheme Utilizing Fault Phase Selection Factors 148 2.4 Summary 172 References 172 3 Local Area Protection for Renewable Energy 175 3.1 Introduction 175 3.2 Fault Transient Characteristics of Renewable Energy Sources 176 3.2.1 Mathematical Model and LVRT Characteristics of DFIG 177 3.2.2 DFIG Fault Transient Characteristics When the Crowbar Protection Is Not Put into Operation 178 3.2.3 DFIG Fault Transient Characteristics When the Crowbar Protection Is Put into Operation 211 3.3 Local Area Protection for Centralized Renewable Energy 230 3.3.1 Connection Form of a Wind Farm and its Protection Configuration 231 3.3.2 Adaptive Distance Protection Scheme for Wind Farm Collector Lines 233 3.3.3 Differential Protection Scheme for Wind Farm Outgoing Transmission Line 239 3.4 Local Area Protection for Distributed Renewable Energy 248 3.4.1 Adaptive Protection Approach for Distribution Network Containing Distributed Generation 248 3.4.2 Islanding Detection Method 255 3.5 Summary 269 References 270 4 Topology Analysis 273 4.1 Introduction 273 4.2 Topology Analysis for Inner Substation 273 4.2.1 Characteristic Analysis of the Main Electrical Connection 274 4.2.2 Topology Analysis Method Based on Main Electrical Wiring Characteristics 275 4.2.3 Scheme Verification 278 4.3 Topology Analysis for Inter-substation 284 4.3.1 Static Topology Analysis for Power Network 285 4.3.2 Topology Update for Power Network 287 4.3.3 Scheme Verification 291 4.4 False Topology Identification 294 4.4.1 Road-Loop Equation 294 4.4.2 Analysis of the Impacts of Topology Error and Undesirable Data on Branch Current 296 4.4.3 Topology Error Identification Method Based on Road-loop Equation 300 4.4.4 Scheme Verification 301 4.5 Summary 315 References 316 5 Substation Area Protection 317 5.1 Introduction 317 5.2 Substation Area Protection Based on Electrical Information 317 5.2.1 Substation Area Regionalization 318 5.2.2 Typical Fault Cases 323 5.2.3 Scheme Performance Analysis 326 5.3 Substation Area Protection Based on Operating Signals 327 5.3.1 Setting Principle of Adaptive Current Protection 327 5.3.2 Supporting Degree Calculation Method 330 5.3.3 Substation Area Current Protection Algorithm 334 5.3.4 Scheme Verification 338 5.4 Summary 346 References 346 6 Wide Area Protection 347 6.1 Introduction 347 6.2 Wide Area Protection Using Electrical Information 347 6.2.1 Wide-Area Protection Using Fault Power Source Information 348 6.2.2 Wide-Area Protection Using Fault Network Information 358 6.2.3 Wide-Area Protection Suitable for Multiple Fault Identification 369 6.3 Wide Area Protection Using Operating Signals 375 6.3.1 Wide-Area Protection Based on Distance Protection Operational Signal 376 6.3.2 Wide-Area Protection Based on Current Protection Operational Signal 393 6.3.3 Wide-Area Protection Based on Virtual Impedance of Fault Component 406 6.4 Wide Area Tripping Strategy 419 6.4.1 Tripping Strategy Based on Directional Weighting 419 6.4.2 Simulation Verification 428 6.5 Summary 432 References 433 Appendices 435 Index 439

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Book SynopsisThe expanded fourth edition of the book that offers an essential introduction to laser technology and the newest developments in the field The revised and updated fourth edition of Understanding Lasers offers an essential guide and introduction that explores how lasers work, what they do, and how they are applied in the real world. The authora Fellow of The Optical Societyreviews the key concepts of physics and optics that are essential for understanding lasers and explains how lasers operate. The book also contains information on the optical accessories used with lasers. Written in non-technical terms, the book gives an overview of the wide-variety laser types and configurations. Understanding Lasers covers fiber, solid-state, excimer, helium-neon, carbon dioxide, free-electron lasers, and more. In addition, the book also explains concepts such as the difference between laser oscillation and amplification, the importance of laser gain, and tunableTable of ContentsPreface xiii CHAPTER 1 Introduction and Overview 1 1.1 Lasers, Optics, and Photonics 1 1.2 Understanding the Laser 3 1.3 What Is a Laser? 4 1.4 Laser Materials and Types 8 1.5 Optical Properties of Laser Light 10 1.6 How Lasers Are Used? 14 1.7 What Have We Learned? 17 CHAPTER 2 Physical Basics 21 2.1 Electromagnetic Waves and Photons 21 2.2 Quantum and Classical Physics 29 2.3 Interactions of Light and Matter 39 2.4 Basic Optics and Simple Lenses 47 2.5 Fiber Optics 51 2.6 What Have We Learned? 54 CHAPTER 3 How Lasers Work 59 3.1 Building a Laser 59 3.2 Producing a Population Inversion 60 3.3 Resonant Cavities 66 3.4 Laser Beams and Resonance 73 3.5 Wavelength Selection and Tuning 81 3.6 Laser Excitation and Efficiency 85 3.7 What Have We Learned? 89 CHAPTER 4 Laser Characteristics 95 4.1 Coherence 95 4.2 Laser Wavelengths 98 4.3 Properties of Laser Beams 103 4.4 Laser Power 108 4.5 Laser Efficiency 110 4.6 Pulse Characteristics 115 4.7 Polarization 120 4.8 What Have We Learned? 121 CHAPTER 5 Optics, Laser Accessories, and Measurements 127 5.1 Classical Optical Devices 127 5.2 Optical Materials 136 5.3 Optical Coatings and Filters 141 5.4 Beam Delivery, Direction, and Propagation 145 5.5 Mounting and Positioning Equipment 148 5.6 Nonlinear Optics 149 5.7 Beam Modulation and Output Control 156 5.8 Measurements in Optics 159 5.9 What Have We Learned? 164 CHAPTER 6 Laser Types, Features, and Enhancements 169 6.1 Perspectives on Laser Types 169 6.2 Laser Media 171 6.3 Pumping and Energy Storage 177 6.4 Laser Pulse Characteristics 182 6.5 Wavelength Conversion 195 6.6 Laser Oscillators and Optical Amplifiers 201 6.7 Wavelength Options 207 6.8 Laser-Like Light Sources 209 6.9 What Have We Learned? 211 CHAPTER 7 Gas Lasers 217 7.1 The Gas-Laser Family 217 7.2 Gas-Laser Basics 218 7.3 Helium–Neon Lasers 225 7.4 Argon- and Krypton-Ion Lasers 229 7.5 Metal-Vapor Lasers 232 7.6 Carbon Dioxide Lasers 235 7.7 Excimer Lasers 240 7.8 Nitrogen Lasers 243 7.9 Chemical Lasers 243 7.10 Other Gas Lasers 246 7.11 What Have We Learned? 247 CHAPTER 8 Solid-State Lasers 253 8.1 What Is a Solid-State Laser? 253 8.2 Solid-State Laser Materials 258 8.3 Solid-State Laser Configurations 265 8.4 Major Solid-State Laser Materials 271 8.5 Optically Pumped Semiconductor Lasers 284 8.6 Broadband and Tunable Solid-State Lasers 288 8.7 Pulsed Solid-State Lasers 294 8.8 What Have We Learned? 295 CHAPTER 9 Fiber Lasers and Amplifiers 301 9.1 What Are Fiber Lasers? 301 9.2 Optical Fiber Structures 306 9.3 Fiber Laser Design and Efficiency 310 9.4 Rare-Earth-Doped Fiber Lasers 318 9.5 Rare-Earth-Doped Fiber Amplifiers 328 9.6 Raman Fiber Lasers and Amplifiers 332 9.7 What Have We Learned? 335 CHAPTER 10 Diode and Other Semiconductor Lasers 341 10.1 Types of Semiconductor Lasers 341 10.2 Development of Diode Lasers 342 10.3 Semiconductor Basics 344 10.4 Comparing LED and Diode-Laser Emission 353 10.5 Confining Light and Current 359 10.6 Edge-Emitting Diode Lasers 370 10.7 Surface-Emitting Diode Lasers 375 10.8 Optical Properties of Diode Lasers 379 10.9 Diode-Laser Materials and Wavelengths 381 10.10 Quantum Cascade Lasers and Related Types 390 10.11 What Have We Learned? 393 CHAPTER 11 Other Lasers and Laser-Like Sources 399 11.1 Tunable Dye Lasers 399 11.2 Optical Parametric Sources 404 11.3 Supercontinuum Sources 408 11.4 Frequency Combs 408 11.5 Extreme Ultraviolet Sources 410 11.6 Free-Electron Lasers 416 11.7 What Have We Learned? 420 CHAPTER 12 Low-Power Laser Applications 425 12.1 Advantages of Laser Light 426 12.2 Reading with Lasers 433 12.3 Optical Disks and Data Storage 437 12.4 Laser Printing 440 12.5 Lasers in Fiber-Optic Communications 442 12.6 Laser Measurement 447 12.7 Laser Light Shows, Pointers, and Projection Displays 453 12.8 Low-Power Defense Applications 456 12.9 Sensing and Spectroscopy 459 12.10 Holography 464 12.11 Other Low-Power Applications 468 12.12 What Have We Learned? 469 CHAPTER 13 High-Power Laser Applications 475 13.1 High- Versus Low-Power Laser Applications 475 13.2 Attractions of High-Power Lasers 476 13.3 Important Considerations and Trends 477 13.4 Materials Working 481 13.5 Additive Manufacturing and Three-Dimensional Printing 489 13.6 Semiconductor Electronics Fabrication 491 13.7 Laser Medical Treatment 493 13.8 Photochemistry and Isotope Separation 501 13.9 Laser-Driven Nuclear Fusion 503 13.10 High-Energy Laser Weapons 505 13.11 What Have We Learned? 510 CHAPTER 14 Lasers in Research 515 14.1 Lasers Open New Opportunities 515 14.2 Laser Spectroscopy 516 14.3 Manipulating Tiny Objects 521 14.4 Atom Lasers and Bose–Einstein Condensates 522 14.5 Detection of Gravitational Waves 524 14.6 Laser Guide Stars for Astronomy 525 14.7 Slow Light 526 14.8 Nanoscale Lasers 527 14.9 Strange Lasers 529 14.10 Extreme Power Ultrashort Pulse Lasers 530 14.11 X-Ray Free-Electron Lasers 535 14.12 Other Emerging Research 536 14.13 What Have We Learned? 538 Answers to Quiz Questions 543 Appendix A: Laser Safety 547 Appendix B: Handy Numbers and Formulas 553 Appendix C: Resources and Suggested Readings 557 Glossary 561 Index 575

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Book SynopsisSystematically discusses the growth method, material properties, and applications for key semiconductor materials MOVPE is a chemical vapor deposition technique that produces single or polycrystalline thin films. As one of the key epitaxial growth technologies, it produces layers that form the basis of many optoelectronic components including mobile phone components (GaAs), semiconductor lasers and LEDs (III-Vs, nitrides), optical communications (oxides), infrared detectors, photovoltaics (II-IV materials), etc. Featuring contributions by an international group of academics and industrialists, this book looks at the fundamentals of MOVPE and the key areas of equipment/safety, precursor chemicals, and growth monitoring. It covers the most important materials from III-V and II-VI compounds to quantum dots and nanowires, including sulfides and selenides and oxides/ceramics. Sections in every chapter of Metalorganic Vapor Phase Epitaxy (MOVPE): Growth, Materials Table of ContentsList of Contributors xv Foreword xvii Series Preface xix Preface xxi Safety and Environment Disclaimer xxiii 1 Introduction to Metalorganic Vapor Phase Epitaxy 1S.J.C. Irvine and P. Capper 1.1 Historical Background of MOVPE 1 1.2 Basic Reaction Mechanisms 4 1.3 Precursors 8 1.4 Types of Reactor Cell 9 1.5 Introduction to Applications of MOVPE 11 1.5.1 AlN for UV Emitters 11 1.5.2 GaAs/AlGaAs VCSELS 11 1.5.3 Multijunction Solar Cells 12 1.5.4 GaAs and InP Transistors for High‐Frequency Devices 13 1.5.5 Infrared Detectors 14 1.5.6 Photovoltaic and Thermophotovoltaic Devices 14 1.6 Health and Safety Considerations in MOVPE 15 1.7 Conclusions 16 References 16 2 Fundamental Aspects of MOVPE 19G.B. Stringfellow 2.1 Introduction 19 2.2 Thermodynamics 20 2.2.1 Thermodynamics of MOVPE Growth 20 2.2.2 Solid Composition 24 2.2.3 Phase Separation 29 2.2.4 Ordering 31 2.3 Kinetics 35 2.3.1 Mass Transport 35 2.3.2 Precursor Pyrolysis 36 2.3.3 Control of Solid Composition 37 2.4 Surface Processes 40 2.4.1 Surface Reconstruction 41 2.4.2 Atomic‐Level Surface Processes 42 2.4.3 Effects of Surface Processes on Materials Properties 44 2.4.4 Surfactants 46 2.5 Specific Systems 52 2.5.1 AlGaInP 52 2.5.2 Group III Nitrides 53 2.5.3 Novel Alloys 56 2.6 Summary 59 References 60 3 Column III: Phosphides, Arsenides, and Antimonides 71H. Hardtdegen and M. Mikulics 3.1 Introduction 71 3.2 Precursors for Column III Phosphides, Arsenides, and Antimonides 73 3.3 GaAs‐Based Materials 74 3.3.1 (AlGa)As/GaAs Properties and Deposition 74 3.3.2 GaInP, (AlGa)InP/GaAs Properties and Deposition 79 3.4 InP‐Based Materials 82 3.4.1 InP Properties and Deposition 82 3.4.2 AlInAs/GaInAs/AlGaInAs Properties and Deposition 83 3.4.3 AlInAs/GaInAs/InP Heterostructures 84 3.4.4 InxGa1–xAsyP1–y Properties and Deposition 84 3.5 Column III Antimonides Properties and Deposition 86 3.5.1 Deposition of InSb, GaSb, and AlSb 87 3.5.2 Deposition of Ternary Column III Alloys (AlGa)Sb and (GaIn)Sb 89 3.5.3 Deposition of Ternary Column V Alloys In(AsSb), GaAsSb 89 3.5.4 Deposition of Quaternary Alloys 90 3.5.5 Epitaxy of Electronic Device Structures 90 3.5.6 Epitaxy of Optoelectronic Device Structures 95 3.6 In Situ Optical Characterization/Growth Control 100 3.7 Conclusions 100 References 101 4 Nitride Semiconductors 109A. Dadgar and M. Weyers 4.1 Introduction 109 4.2 Properties of III‐Nitrides 110 4.3 Challenges in the Growth of III‐Nitrides 111 4.3.1 Lattice and Thermal Mismatch 111 4.3.2 Ternary Alloys: Miscibility and Compositional Homogeneity 113 4.3.3 Gas‐Phase Prereactions 115 4.3.4 Doping of III‐Nitrides 117 4.4 Substrates 120 4.4.1 Heteroepitaxy on Foreign Substrates 122 4.4.2 GaN Growth on Sapphire 125 4.4.3 III‐N Growth on SiC 126 4.4.4 GaN Growth on Silicon 127 4.5 MOVPE Growth Technology 130 4.5.1 Precursors 130 4.5.2 Reactors and In Situ Monitoring 130 4.6 Economic Importance 136 4.6.1 Optoelectronic Devices 137 4.6.2 Electronic Devices 138 4.7 Conclusions 138 References 138 5 Metamorphic Growth and Multijunction III‐V Solar Cells 149N.H. Karam, C.M. Fetzer, X.‐Q. Liu, M.A. Steiner, and K.L. Schulte 5.1 Introduction to MOVPE for Multijunction Solar Cells 149 5.1.1 III‐V PV Solar Cell Opportunities and Applications 149 5.1.2 Metamorphic Multijunction Solar Cells 151 5.1.3 Reactor Technology for Metamorphic Epitaxy 154 5.2 Upright Metamorphic Multijunction (UMM) Solar Cells 154 5.2.1 Introduction and History of Upright Metamorphic Multijunctions 154 5.2.2 MOVPE Growth Considerations of UMM 156 5.2.3 Growth and Device Results 158 5.2.4 Challenges and Future Outlook 162 5.3 Inverted Metamorphic Multijunction (IMM) Solar Cells 162 5.3.1 Introduction and History of Inverted Metamorphic Multijunctions 162 5.3.2 MOVPE Growth Considerations of IMM 164 5.3.3 Growth and Device Results 167 5.3.4 Challenges and Future Outlook 169 5.4 Conclusions 169 References 170 6 Quantum Dots 175E. Hulicius, A. Hospodková, and M. Zíková 6.1 General Introduction to the Topic 175 6.1.1 Definition and History 175 6.1.2 Paradigm of Quantum Dots 176 6.1.3 QD Types 176 6.2 AIIIBV Materials and Structures 178 6.2.1 QDs Embedded in the Structure 178 6.2.2 Semiconductor Materials for Embedded QDs 180 6.3 Growth Procedures 181 6.3.1 Comparison of MBE‐ and MOVPE‐Grown QDs 181 6.3.2 Growth Parameters 182 6.3.3 QD Surrounding Layers 185 6.4 In Situ Measurements 193 6.4.1 Reflectance Anisotropy Spectroscopy of QD Growth 193 6.4.2 Other Supporting In Situ Measurements 197 6.5 Structure Characterization 198 6.5.1 Optical: Photo‐, Magnetophoto‐, Electro‐luminescence, and Spin Detection 198 6.5.2 Microscopies – AFM, TEM, XSTM, BEEM/BEES 200 6.5.3 Electrical: Photocurrent, Capacitance Measurements 202 6.6 Applications 203 6.6.1 QD Lasers, Optical Amplifiers, and LEDs 204 6.6.2 QD Detectors, FETs, Photovoltaics, and Memories 205 6.7 Summary 208 6.8 Future Perspectives 208 Acknowledgment 209 References 209 7 III‐V Nanowires and Related Nanostructures: From Nitrides to Antimonides 217H.J. Joyce 7.1 Introduction to Nanowires and Related Nanostructures 217 7.2 Geometric and Crystallographic Properties of III‐V Nanowires 219 7.2.1 Crystal Phase 219 7.2.2 Growth Direction, Morphology, and Side‐Facets 220 7.3 Particle‐Assisted MOVPE of Nanowires 222 7.3.1 The Phase of the Particle 222 7.3.2 The Role of the Particle 224 7.3.3 Axial and Radial Growth Modes 226 7.3.4 Self‐Assisted Growth 228 7.4 Selective‐Area MOVPE of Nanowires and Nanostructures 228 7.4.1 The Role of the Mask 229 7.4.2 Axial and Radial Growth Modes 230 7.5 Alternative Techniques for MOVPE of Nanowires 231 7.6 Novel Applications of Nanowires 231 7.7 Concluding Remarks 233 References 234 8 Monolithic III/V integration on (001) Si substrate 241B. Kunert and K. Volz 8.1 Introduction 241 8.2 III/V‐Si Interface 243 8.2.1 Si Surfaces 243 8.2.2 Interface Formation in the Presence of Impurities and MO Precursors 247 8.2.3 Atomic III/V on Si Interface Structure 249 8.2.4 Antiphase Domains 251 8.2.5 III/V Growth on Si(001) 252 8.3 Heteroepitaxy of Bulk Layers on Si 255 8.3.1 Lattice‐Matched Growth on Si 257 8.3.2 Metamorphic Growth on Blanket Si 258 8.3.3 Selective‐Area Growth (SAG) on Si 264 8.4 Conclusions 282 References 282 9 MOVPE Growth of Cadmium Mercury Telluride and Applications 293C.D. Maxey, P. Capper, and I.M. Baker 9.1 Requirement for Epitaxy 293 9.2 History 294 9.3 Substrate Choices 295 9.3.1 Orientation 296 9.3.2 Substrate Material 296 9.4 Reactor Design 297 9.4.1 Process Abatement Systems 298 9.5 Process Parameters 299 9.6 Metalorganic Sources 299 9.7 Uniformity 300 9.8 Reproducibility 302 9.9 Doping 302 9.10 Defects 304 9.11 Annealing 307 9.12 In Situ Monitoring 308 9.13 Background for Applications of MOVPE MCT 308 9.13.1 Introduction to Infrared Imaging and Atmospheric Windows 308 9.13.2 MCT Infrared Detector Market in the Modern Era 309 9.14 Manufacturing Technology for MOVPE Photodiode Arrays 311 9.14.1 Mesa Heterojunction Devices (MHJ) 311 9.14.2 Wafer‐Scale Processing 312 9.15 Advanced MCT Technologies 312 9.15.1 Small‐Pixel Technology 313 9.15.2 Higher Operating Temperature (HOT) Device Structures 313 9.15.3 Two‐Color Array Technology 314 9.15.4 Nonequilibrium Device Structures 316 9.16 MOVPE MCT for Scientific Applications 316 9.16.1 Linear‐Mode Avalanche Photodiode Arrays (LmAPDs) in MOVPE 316 9.17 Conclusions and Future Trends for MOVPE MCT Arrays 320 Definitions 321 References 322 10 Cadmium Telluride and Related II‐VI Materials 325G. Kartopu and S.J.C. Irvine 10.1 Introduction and Historical Background 325 10.2 CdTe Homoepitaxy 327 10.3 CdTe Heteroepitaxy 327 10.3.1 InSb 327 10.3.2 Sapphire 328 10.3.3 GaAs 329 10.3.4 Silicon 330 10.4 Low‐Temperature Growth and Alternative Precursors 330 10.5 Photoassisted MOVPE 332 10.6 Plasma‐Assisted MOVPE 333 10.7 Polycrystalline MOCVD 333 10.8 In Situ Monitoring of CdTe 334 10.8.1 Mechanisms for Laser Reflectance (LR) Monitoring 335 10.9 MOCVD of CdTe for Planar Solar Cells 337 10.9.1 CdS and CdZnS Window Layers 338 10.9.2 CdTe Absorber Layer 338 10.9.3 CdCl2 Treatment Layer 342 10.9.4 Photovoltaic Planar Devices 343 10.10 Core‐Shell Nanowire Photovoltaic Devices 345 10.11 Inline MOCVD for Scaling of CdTe 347 10.12 MOCVD of CdTe for Radiation Detectors 350 References 351 11 ZnO and Related Materials 355V. Muñoz‐Sanjosé and S.J.C. Irvine 11.1 Introduction 355 11.2 Sources for the MOCVD Growth of ZnO and Related Materials 356 11.2.1 Metalorganic Zinc Precursors 356 11.2.2 Metalorganic Cadmium Precursors 360 11.2.3 Metalorganic Magnesium Precursors 360 11.2.4 Precursors for Oxygen 361 11.2.5 Precursors for Doping 363 11.3 Substrates for the MOCVD Growth of ZnO and Related Materials 364 11.3.1 ZnO Single Crystals and ZnO Templates as Substrates 365 11.3.2 Sapphire (Al2O3) 367 11.3.3 Silicon 369 11.3.4 Glass Substrates 372 11.4 Some Techniques for the MOCVD Growth of ZnO and Related Materials 373 11.4.1 Atmospheric and Low‐Pressure Conditions in Conventional MOCVD Systems 374 11.4.2 MOCVD‐Assisted Processes 376 11.5 Crystal Growth of ZnO and Related Materials 380 11.5.1 Crystal Growth by MOCVD of ZnO Layers 380 11.5.2 Crystal Growth of ZnO Nanostructures 393 11.5.3 Crystal Growth of ZnO‐Related Materials 398 11.5.4 Doping of ZnO and Related Materials 400 11.6 Conclusions 405 Acknowledgments 406 References 406 12 Epitaxial Systems for III‐V and III‐Nitride MOVPE 423W. Lundin and R. Talalaev 12.1 Introduction 423 12.2 Typical Engineering Solutions Inside MOVPE Tools 424 12.2.1 Gas‐Blending System 424 12.2.2 Exhaust System 433 12.2.3 Reactors 435 12.3 Reactors for MOVPE of III‐V Materials 438 12.3.1 General Features of III‐V MOVPE 438 12.3.2 From Simple Horizontal Flow to Planetary Reactors 439 12.3.3 Close‐Coupled Showerhead (CCS) Reactors 445 12.3.4 Rotating‐Disk Reactors 447 12.4 Reactors for MOVPE of III‐N Materials 451 12.4.1 Principal Differences between MOVPE of Classical III‐Vs and III‐Ns 451 12.4.2 Rotating‐Disk Reactors 454 12.4.3 Planetary Reactors 455 12.4.4 CCS Reactors 458 12.4.5 Horizontal Flow Reactors for III‐N MOVPE 459 12.5 Twenty‐Five Years of Commercially Available III‐N MOVPE Reactor Evolution 462 References 464 13 Ultrapure Metal‐Organic Precursors for MOVPE 467D.V. Shenai‐Khatkhate 13.1 Introduction 467 13.1.1 MOVPE Precursor Classes and Impurities 468 13.2 Stringent Requirements for Suitable MOVPE Precursors 472 13.3 Synthesis and Purification Strategies for Ultrapure MOVPE Precursors 472 13.3.1 Synthetic Strategies for Ultrapure MOVPE Precursors 472 13.3.2 Purification Strategies for MOVPE Precursors 476 13.4 MOVPE Precursors for III‐V Compound Semiconductors 483 13.4.1 Group III MOVPE Precursors 483 13.4.2 Group V MOVPE Precursors 488 13.5 MOVPE Precursors for II‐VI Compound Semiconductors 493 13.5.1 Group II MOVPE Precursors 493 13.5.2 Group VI MOVPE Precursors 496 13.6 MOVPE Dopants for Compound Semiconductors 499 13.7 Environment, Health, and Safety (EHS) Aspects of MOVPE Precursors 500 13.7.1 General Aspects and Considerations 500 13.7.2 Employee and Environment Exposure Aspects 501 13.7.3 Employee and Workplace Exposure Limits 502 13.8 Conclusions and Future Trends 502 Acknowledgments 503 References 503 14 Future Aspects of MOCVD Technology for Epitaxial Growth of Semiconductors 507T. Detchprohm, J.‐H. Ryou, X. Li, and R.D. Dupuis 14.1 Introduction – Looking Back 507 14.2 Future Equipment Development 510 14.2.1 Production MOCVD 510 14.2.2 R&D MOCVD 511 14.2.3 MOCVD for Ultrawide‐Bandgap III‐Nitrides 512 14.2.4 MOCVD for Emerging Materials 513 14.2.5 Democratization of MOCVD 514 14.3 Future Applications for MOCVD Research in Semiconductor Materials 515 14.3.1 Heteroepitaxy 515 14.3.2 Nanostructural Materials 527 14.3.3 Poly, Amorphous, and Other Materials 532 14.4 Past, Present, and Future Commercial Applications 535 14.4.1 LEDs 535 14.4.2 Lasers 536 14.4.3 OEICs 536 14.4.4 High‐Speed Electronics 536 14.4.5 High‐Power Electronics 537 14.4.6 Solar Cells 537 14.4.7 Detectors 538 14.5 Summary and Conclusions 538 Acknowledgments 539 References 539 Index 549

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Book SynopsisTelecommunication Services provides aholistic approach to understand telecommunications systems by addressing the emergence and domination of new digital services, consumer and economic dynamics, and the creation of content by service providers. Includes services, underlying technologies, and internal capabilities for social network advertising Covers market dynamics that determine the successes and failures of service offerings Discusses the impact of smartphones (iPhone launch) on the telecommunications and mobile device industry Table of ContentsForeword xiVinton G. Cerf Preface xiii Acknowledgments xv List of Contributors xvii 1. The Evolving Voice Services: From Circuit Switching to Voice-Over LTE/FTTH) 1 1.1 Customer Need: Remote Communication 1 1.2 FTTH Voice 2 1.3 Voice-Over LTE (VoLTE) 2 1.4 Voice-Over WiFi 4 1.5 High-Definition (HD) Voice 5 1.6 Over-the-Top Substitutes 5 2. Internet Services: From Broadband to Ultrabroadband 9 2.1 Customer Need: Connectivity and Social Inclusion 10 2.2 Fixed Lines: Deploying Fiber Closer to Customer Premises: xDSL, Cable, FTTH 11 2.3 Mobile: 4G LTE/LTE-Advanced 19 2.4 WiFi AC (Gigabit) 23 2.5 Universal Access 23 3. Convergence: Bundling Fixed Line and Mobile Services 31 3.1 Customer Need: One-Stop Shop 31 3.2 Fixed Line and Mobile Service Bundles 31 3.3 Integrated Operators 32 4. Devices: Smartphones 37 4.1 Customer Need: Mobility 37 4.2 Vendors 38 4.3 Operating System Duopoly 39 4.4 Hardware Specifications 40 5. The Evolving Pay TV 51Francisco Saez and Joaquín M. Lopez Muñoz 5.1 Customer Need: Entertainment 51 5.2 Content Wars 53 5.3 Aggregation versus Diversity 56 5.4 The Role of Advertising 57 5.5 Technology: Satellite, Cable, and IPTV 58 5.6 Pay TV Technicall Key Components 58 5.7 Evolution of Interactive Pay TV Technologies 60 5.8 Video Definition 64 6. Enterprise: From Machine-to-Machine Connectivity Toward Internet of Things 69 6.1 Customer Need: Remote Automation 70 6.2 Basic Connectivity and Managed Connectivity 71 6.3 Low-Power Wide Area: LTE-MTC and Alternatives 77 6.4 Applications: Toward Internet of Things 86 7. IT: Cloud 103Stefan Wesner 7.1 Global Trends Driving the Cloud Evolution 104 7.2 Virtualization as Enabling Technology 105 7.3 The Layered Cloud Model 106 7.4 Advanced Cloud Models 111 7.5 Future Cloud Models 113 7.6 Conclusion and Summary 115 8. Emerging Markets: Mobile Money for the Unbanked 117 8.1 Customer Need: Remote Payments 117 8.2 Large Unbanked Population in Emerging Markets 118 8.3 Very High Penetration of Mobile Based on Feature Phones 129 8.4 Services: Remittances and Payments 137 9. Value-Added Consumer Services 143Jesus Llamazares Alberola 9.1 Introduction 143 9.2 Disruption is the New “Karma” 143 9.3 Adjacent Industries Joining Multilayered Value Chain 145 9.4 Telco’s Role and Challenges in the New Paradigm 146 9.5 But What do we Understand by VAS Today? 148 9.6 So What’s the Future for VAS and, Thus, for Telcos? 152 10. Mobile Virtual Network Operators/Second Brands 155Jaime Bustillo 10.1 From Oligopoly to Marketplace 156 10.2 MVNO Ecosystem: End Customer Facing or MVNOs 157 10.3 MVNO Ecosystem: Technology Enablers, MVNE, and MVNA 160 11. Digital Home 163 11.1 Introduction to Home Automation 163 11.2 Evolution to Digital Home 165 11.3 Home Automation: Control Network 170 11.4 Digital Home Networks 179 12. Videoconference and Telework 185 12.1 Customer Need: Teletransport 185 12.2 Videoconference 186 12.3 Telework 195 Index 205

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Book SynopsisThe invaluable handbook for acing your on-camera appearance On-Camera Coach is your personal coach for becoming great on camera. From Skype interviews and virtual conferences to shareholder presentations and television appearances, this book shows you how to master the art of on-camera presentation to deliver your message clearly, effectively, and with confidence. Fear of public speaking is common, but even the most seasoned speakers freeze in front of a single lensbeing on camera demands an entirely new set of skills above and beyond the usual presentation to an audience you can actually see. It requires special attention to the way you move, the way you speak, and even the way you dress. This book provides the guidance and tools you need to ace it every time. Video is powerful, and it is everywhere; corporate YouTube channels, webinars, virtual meetings, TedTalks, and more are increasingly turning the lens on those who typically remain behind the scenesTable of ContentsWiley & SAS Business Series ii Preface xvii Acknowledgments xix Section One The Inescapable Reality—We All Have to Communicate through a Camera 1 Chapter 1 Why You Need to Read This Book 3 The Power and Pervasiveness of Video 5 The Decline of the Professional Spokesperson 6 The Global Communication Tool of Choice 7 Hiring by Skype 8 The Perils of Video 9 How Reading This Book Can Improve Your On-Camera Performance 9 What You Will Need 10 Topics to Be Discussed 10 Chapter Takeaways 11 Notes 11 Chapter 2 Why the Camera Changes Everything 13 My “Aha!” Moment 16 A Camera Changes Everything 17 No Immediate Feedback 17 Your Own Worst Critic 18 Recorded for Posterity 19 Unfamiliar Territory 20 The Archenemy of Performance Success: You 21 The Key to On-Camera Success: Authenticity 22 Chapter Takeaways 24 Section Two The MVPs of Performance Success 25 Chapter 3 M—Mental Mind-set: The Prep before the Performance 27 Reaching the Real Audience 28 Visualize the Viewer 30 Video Chat: Now You See Me, Now You Don’t 30 Embrace Your Nervousness 32 Passion Play 33 Beware of Brain Cramps 33 The Bottom Line: It’s Not about You 35 Chapter Takeaways 38 Note 39 Chapter 4 V—Vocal Variety: Pacing and Pausing with Purpose 41 The Musicality of Your Delivery—What’s Your Range? 42 What Is Vocal Variety? 42 Natural versus On-Camera Inflection 43 Setting Your Pace with the Viewer in Mind 44 Finishing Your Thoughts 45 Using the Power of the Pause 45 Pause for You 45 Filler Words as Placeholders 47 Pause for Them 47 The Lowdown on Uptalk 49 The Most Common Uptalk Trouble Spot 50 Chapter Takeaways 54 Note 54 Chapter 5 P—Physical Factors: On-Camera Movement with Meaning 55 On-Camera Gesturing: An Out-of-Body Experience 56 Getting Familiar with Frame Size 58 Gestures for a Tight Shot 58 Gestures for a Medium Shot 58 Gestures for a Wide Shot 59 Gestures as a Retention Tool 60 The Role of Off-Camera Movement 61 Posture Pointers 61 Standing While on Camera 62 The Metronome Effect 62 Going for a Walk 62 Sitting While on Camera 63 Crossed Legs 64 Leaning In or Out 64 Step In to Start 65 Making Eye Contact When You Can’t See Your Audience 66 Look Away 66 Performance Pitfalls: Eye Contact Errors 67 Vary Your Angle 68 Look Up 68 Chapter Takeaways 72 Notes 72 Section Three Ready to Wear . . . or Not 73 Chapter 6 Looking the Part—Wardrobe 101 75 Match Audience Expectations 77 Boring Is Best 78 Spin the Color Wheel 78 Special Consideration: Green-Screen Shoots 79 Solids: A Solid Choice 80 Putting on the Pounds 82 Dress Right for the Mic 82 Pack Placement 83 Microphone Placement 83 Jewelry Jukebox and Light Show 84 Your Fifth Appendage: A Smartphone 85 Additional Considerations for Men 85 Sock Style 86 The Uniform Look 87 To Button or Not to Button? 87 Chapter Takeaways 88 Notes 88 Chapter 7 Hair and Makeup 89 Hair Hassles 91 On-Camera Makeup Musts for Women 92 What You Need in Your Kit 93 Moisturizer 93 Foundation 93 Powder 94 Eye Makeup 94 Cheeks 94 Lip Color 95 Makeup for Men 95 Glasses or No Glasses 96 Chapter Takeaways 97 Section Four Best Practices for Creating Your On-Camera Message 99 Chapter 8 Organizing for the Ear 101 The Rule of Three 102 Applying the Rule of Three On Camera 103 Rule of Three via Skype 104 Your Core Message 105 The Rule of Three Expanded 106 Repetition, Repetition, Repetition 107 Chapter Takeaways 108 Note 108 Chapter 9 Writing for the Spoken Word 109 The Challenges of Reading Written Prose Aloud 110 Why the Whisper Test Won’t Work 111 Writing Tip 1: Keep It Short 111 Writing Tip 2: Don’t Fear the Grammar Police 112 Writing Tip 3: See Spot . . . Be Bored 113 Exercises for Writing the Way You Speak 113 Chapter Takeaways 116 Note 117 Section Five How to Read without Sounding Like You Are 119 Chapter 10 Marking Your Script 121 Step One: Smooth Out the Script 123 Step Two: Add Phonetics Where Appropriate 123 Step Three: Mark with Meaning 125 New vs. Old 126 The Name Stress Principle 128 How to Mark Your Copy for Emphasis 129 Emphasis Obstacles 130 Beware of Connotations 130 Too Much Stress 131 Step Four: Place Your Pauses 131 The Short Pause 132 The Power Pause 132 Marking Your Pauses 134 Pause Practice Example 134 Pause Pitfalls 135 It All Comes Down to This 136 Chapter Takeaways 137 Script Marking Exercises Answer Key 138 Notes 140 Chapter 11 Tackling the Teleprompter 141 Lessons Learned from Michael Bay’s Implosion 143 Lesson 1: Know Your Content 143 Lesson 2: Know Your Script 143 Lesson 3: Stay in the Moment 144 Teleprompter-Friendly Copy: Best Practices 144 Read Your Script in the Prompter before Your Performance 145 Effective Visual Cues in Teleprompter Copy 146 Options for Marking Emphasis 146 Options for Marking Pauses 147 Visual Cues Are Guides, Not Absolutes 149 The Role of the Teleprompter Operator 149 A Second Set of Eyes 150 Adjusting Font Size 150 Following the Leader 150 Editing on the Fly 151 No Mind Reading 151 Adjusting the Read Line 152 Prompter Practice Made Possible 152 The Proliferation of Prompter Software 153 Control the Scroll 153 Watch Yourself 154 Lost in the Teleprompter 154 Chapter Takeaways 155 Note 155 Section Six The Most Common On-Camera Performance Scenarios 157 Chapter 12 Presenting Directly to the Camera in a Studio Setting 159 Considerations for Corporate Video 161 A Lesson from TV News 161 Does Length Matter? 162 How Much Face Time Is Too Much? 163 Preparing for the Shoot 164 Creating Your Content 164 Identifying Your Viewer 164 Writing the Way You Speak 165 Marking for Meaning 165 Practice, Practice, Practice 166 Looking the Part 167 Microphone Matters 167 Hair Issues 168 Getting Rid of Your Fifth Appendage 168 Orienting Yourself to the Studio 169 Meet the Crew 169 The Floor Director 169 The Audio Technician 170 The Camera Operator 171 The Teleprompter Operator 171 The Crew’s Mission 171 Give Yourself the Once-Over 172 Getting Familiar with Your Performance Space 172 The Crew’s Final Prep 173 Pulling Off a Great Performance 173 Stay Focused Despite Distractions 174 The Most Dangerous Part of Your Performance 176 The Runaway Train Ramble 176 Mentally Moving On 177 Stopping the Performance before the Real End 177 Reviewing Your Performance 178 Chapter Takeaways 178 Chapter 13 Videoconferencing and Interviews via Video Chat 181 Changes in Where and How You Work 182 Hiring by Skype 184 Travel Cost Savings 185 Fewer Scheduling Headaches 185 Why You Want to Turn on Your Webcam 186 Best Practices for VC 187 Technical Considerations 187 Setting Considerations 189 Performance Considerations 191 Recording a Videoconference 193 Chapter Takeaways 197 Notes 198 Chapter 14 Webcasts—Best Practices for Panelists and Moderators 199 Why a Webcast Is Easier to Master 200 Best Practices for Panelists 202 Prepare Your Points 202 Plan Your Wardrobe 203 Take Advantage of Rehearsal Time 203 Focus on the Action 204 Where You Should Look 205 When Someone Asks You a Question 205 When Presenting Uninterrupted to Viewers 205 When Others Are Speaking 206 Opting Out of Using a Teleprompter 207 Handling the Unexpected Question 208 Best Practices for Moderators 208 Directing the Conversation 209 Preparing to Be a Moderator 209 Encouraging the Conversation 210 Being the Ultimate Editor 211 Staying Hydrated 212 Chapter Takeaways 213 Notes 213 Chapter 15 Broadcast Interview Basics 215 Before the TV Interview 216 Find Out the Focus 217 Simplify Your Talking Points 218 Seek to Speak in Sound Bites 219 Practice with a Peer 219 During the TV Interview 220 Establishing a Friendly Rapport 220 Checking Yourself in the Mirror 220 Realizing When the Camera Is On 221 Orally Editing Your Sound Bite 221 Controlling the Controllables 222 Pause to Ponder 222 Press Your Own Reset Button 222 Keep Your Cool 223 Answer Every Question as Best You Can 223 After the TV Interview 224 Interviews by Satellite 225 Introducing the IFB 226 Managing the Monitor 226 Waiting for the All-Clear 227 Chapter Takeaways 229 Notes 230 Conclusion: Embrace Communicating through the Camera 231 About the Author 233 Index 235

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