WAP (wireless) technology Books

Book SynopsisA highly interdisciplinary overview of the emerging topic of the Quantum Internet. Current and future quantum technologies are covered in detail, in addition to their global socio-economic impact. Written in an engaging style and accessible to graduate students in physics, engineering, computer science and mathematics.Trade Review'This book explores the technical and socioeconomic aspects of a future quantum internet … The volume will be a valuable acquisition for any institution supporting research in quantum computing or, more broadly, the emerging science and engineering of quantum information … Highly recommended.' M. C. Ogilvie, Choice ConnectTable of ContentsPart I. Introduction: 1. Foreword; 2. Introduction. Part II. Classical Networks: 3. Mathematical representation of networks; 4. Network topologies; 5. Network algorithms. Part III. Quantum Networks: 6. Quantum channels; 7. Optical encoding of quantum information; 8. Errors in quantum networks; 9. Quantum cost vector analysis; 10. Routing strategies; 11. Interconnecting and interfacing quantum networks; 12. Optical routers; 13. Optical stability in quantum networks. Part IV. Protocols for the Quantum Internet: 14. State preparation; 15. Measurement; 16. Evolution; 17. High-level protocols. Part V. Entanglement Distribution: 18. Entanglement – The ultimate quantum resource; 19. Quantum repeater networks; 20. The irrelevance of latency; 21. The quantum Sneakernet™. Part VI. Quantum Cryptography: 22. What is security?; 23. Classical cryptography; 24. Attacks on classical cryptography; 25. Bitcoin and the blockchain; 26. Quantum cryptography; 27. Attacks on quantum cryptography. Part VII. Quantum Computing: 28. Models for quantum computation; 29. Quantum algorithms. Part VIII. Cloud Quantum Computing: 30. The Quantum Cloud™; 31. Encrypted cloud quantum computation. Part IX. Economics and Politics: 32. Classical-equivalent computational power and computational scaling functions; 33. Per-qubit computational power; 34. Time-sharing; 35. Economic model assumptions; 36. Network power; 37. Network value; 38. Rate of return; 39. Market competitiveness; 40. Cost of computation; 41. Arbitrage-free time-sharing model; 42. Problem size scaling functions; 43. Quantum computational leverage; 44. Static computational return; 45. Forward contract pricing model; 46. Political leverage; 47. Economic properties of the qubit marketplace; 48. Economic implications; 49. Game theory of the qubit marketplace. Part X. Essays: 50. The era of quantum supremacy; 51. The global virtual quantum computer; 52. The economics of the quantum internet; 53. Security implications of the global quantum internet; 54. Geostrategic quantum politics; 55. The quantum ecosystem. Part XI. The End: 56. Conclusion. References. Index.

Read more less

Book SynopsisCovers theoretical and practical aspects related to the behavioral modelling and predistortion of wireless transmitters and power amplifiers. It includes simulation software that enables the users to apply the theory presented in the book.Table of ContentsAbout the Authors xi Preface xiii Acknowledgments xv 1 Characterization of Wireless Transmitter Distortions 1 1.1 Introduction 1 1.1.1 RF Power Amplifier Nonlinearity 2 1.1.2 Inter-Modulation Distortion and Spectrum Regrowth 2 1.2 Impact of Distortions on Transmitter Performances 6 1.3 Output Power versus Input Power Characteristic 9 1.4 AM/AM and AM/PM Characteristics 10 1.5 1 dB Compression Point 12 1.6 Third and Fifth Order Intercept Points 15 1.7 Carrier to Inter-Modulation Distortion Ratio 16 1.8 Adjacent Channel Leakage Ratio 18 1.9 Error Vector Magnitude 19 References 21 2 Dynamic Nonlinear Systems 23 2.1 Classification of Nonlinear Systems 23 2.1.1 Memoryless Systems 23 2.1.2 Systems with Memory 24 2.2 Memory in Microwave Power Amplification Systems 25 2.2.1 Nonlinear Systems without Memory 25 2.2.2 Weakly Nonlinear and Quasi-Memoryless Systems 26 2.2.3 Nonlinear System with Memory 27 2.3 Baseband and Low-Pass Equivalent Signals 27 2.4 Origins and Types of Memory Effects in Power Amplification Systems 29 2.4.1 Origins of Memory Effects 29 2.4.2 Electrical Memory Effects 30 2.4.3 Thermal Memory Effects 33 2.5 Volterra Series Models 38 References 40 3 Model Performance Evaluation 43 3.1 Introduction 43 3.2 Behavioral Modeling versus Digital Predistortion 43 3.3 Time Domain Metrics 46 3.3.1 Normalized Mean Square Error 46 3.3.2 Memory Effects Modeling Ratio 47 3.4 Frequency Domain Metrics 48 3.4.1 Frequency Domain Normalized Mean Square Error 48 3.4.2 Adjacent Channel Error Power Ratio 49 3.4.3 Weighted Error Spectrum Power Ratio 50 3.4.4 Normalized Absolute Mean Spectrum Error 51 3.5 Static Nonlinearity Cancelation Techniques 52 3.5.1 Static Nonlinearity Pre-Compensation Technique 52 3.5.2 Static Nonlinearity Post-Compensation Technique 56 3.5.3 Memory Effect Intensity 59 3.6 Discussion and Conclusion 61 References 62 4 Quasi-Memoryless Behavioral Models 63 4.1 Introduction 63 4.2 Modeling and Simulation of Memoryless/Quasi-Memoryless Nonlinear Systems 63 4.3 Bandpass to Baseband Equivalent Transformation 67 4.4 Look-Up Table Models 69 4.4.1 Uniformly Indexed Loop-Up Tables 69 4.4.2 Non-Uniformly Indexed Look-Up Tables 70 4.5 Generic Nonlinear Amplifier Behavioral Model 71 4.6 Empirical Analytical Based Models 73 4.6.1 Polar Saleh Model 73 4.6.2 Cartesian Saleh Model 74 4.6.3 Frequency-Dependent Saleh Model 76 4.6.4 Ghorbani Model 76 4.6.5 Berman and Mahle Phase Model 77 4.6.6 Thomas–Weidner–Durrani Amplitude Model 77 4.6.7 Limiter Model 78 4.6.8 ARCTAN Model 79 4.6.9 Rapp Model 81 4.6.10 White Model 82 4.7 Power Series Models 82 4.7.1 Polynomial Model 82 4.7.2 Bessel Function Based Model 83 4.7.3 Chebyshev Series Based Model 84 4.7.4 Gegenbauer Polynomials Based Model 84 4.7.5 Zernike Polynomials Based Model 85 References 86 5 Memory Polynomial Based Models 89 5.1 Introduction 89 5.2 Generic Memory Polynomial Model Formulation 90 5.3 Memory Polynomial Model 91 5.4 Variants of the Memory Polynomial Model 91 5.4.1 Orthogonal Memory Polynomial Model 91 5.4.2 Sparse-Delay Memory Polynomial Model 93 5.4.3 Exponentially Shaped Memory Delay Profile Memory Polynomial Model 95 5.4.4 Non-Uniform Memory Polynomial Model 96 5.4.5 Unstructured Memory Polynomial Model 97 5.5 Envelope Memory Polynomial Model 98 5.6 Generalized Memory Polynomial Model 101 5.7 Hybrid Memory Polynomial Model 106 5.8 Dynamic Deviation Reduction Volterra Model 108 5.9 Comparison and Discussion 111 References 113 6 Box-Oriented Models 115 6.1 Introduction 115 6.2 Hammerstein and Wiener Models 115 6.2.1 Wiener Model 116 6.2.2 Hammerstein Model 117 6.3 Augmented Hammerstein and Weiner Models 118 6.3.1 Augmented Wiener Model 118 6.3.2 Augmented Hammerstein Model 119 6.4 Three-Box Wiener–Hammerstein Models 120 6.4.1 Wiener–Hammerstein Model 120 6.4.2 Hammerstein–Wiener Model 120 6.4.3 Feedforward Hammerstein Model 121 6.5 Two-Box Polynomial Models 123 6.5.1 Models’ Descriptions 123 6.5.2 Identification Procedure 124 6.6 Three-Box Polynomial Models 124 6.6.1 Parallel Three-Blocks Model: PLUME Model 124 6.6.2 Three Layered Biased Memory Polynomial Model 125 6.6.3 Rational Function Model for Amplifiers 127 6.7 Polynomial Based Model with I/Q and DC Impairments 128 6.7.1 Parallel Hammerstein (PH) Based Model for the Alleviation of Various Imperfections in Direct Conversion Transmitters 129 6.7.2 Two-Box Model with I/Q and DC Impairments 129 References 130 7 Neural Network Based Models 133 7.1 Introduction 133 7.2 Basics of Neural Networks 133 7.3 Neural Networks Architecture for Modeling of Complex Static Systems 137 7.3.1 Single-Input Single-Output Feedforward Neural Network (SISO-FFNN) 137 7.3.2 Dual-Input Dual-Output Feedforward Neural Network (DIDO-FFNN) 138 7.3.3 Dual-Input Dual-Output Coupled Cartesian Based Neural Network (DIDO-CC-NN) 139 7.4 Neural Networks Architecture for Modeling of Complex Dynamic Systems 140 7.4.1 Complex Time-Delay Recurrent Neural Network (CTDRNN) 141 7.4.2 Complex Time-Delay Neural Network (CTDNN) 142 7.4.3 Real Valued Time-Delay Recurrent Neural Network (RVTDRNN) 142 7.4.4 Real Valued Time-Delay Neural Network (RVTDNN) 144 7.5 Training Algorithms 147 7.6 Conclusion 150 References 151 8 Characterization and Identification Techniques 153 8.1 Introduction 153 8.2 Test Signals for Power Amplifier and Transmitter Characterization 155 8.2.1 Characterization Using Continuous Wave Signals 155 8.2.2 Characterization Using Two-Tone Signals 156 8.2.3 Characterization Using Multi-Tone Signals 157 8.2.4 Characterization Using Modulated Signals 158 8.2.5 Characterization Using Synthetic Modulated Signals 160 8.2.6 Discussion: Impact of Test Signal on the Measured AM/AM and AM/PM Characteristics 160 8.3 Data De-Embedding in Modulated Signal Based Characterization 163 8.4 Identification Techniques 170 8.4.1 Moving Average Techniques 170 8.4.2 Model Coefficient Extraction Techniques 172 8.5 Robustness of System Identification Algorithms 179 8.5.1 The LS Algorithm 179 8.5.2 The LMS Algorithm 179 8.5.3 The RLS Algorithm 180 8.6 Conclusions 181 References 181 9 Baseband Digital Predistortion 185 9.1 The Predistortion Concept 185 9.2 Adaptive Digital Predistortion 188 9.2.1 Closed Loop Adaptive Digital Predistorters 188 9.2.2 Open Loop Adaptive Digital Predistorters 189 9.3 The Predistorter’s Power Range in Indirect Learning Architectures 191 9.3.1 Constant Peak Power Technique 193 9.3.2 Constant Average Power Technique 193 9.3.3 Synergetic CFR and DPD Technique 194 9.4 Small Signal Gain Normalization 194 9.5 Digital Predistortion Implementations 201 9.5.1 Baseband Digital Predistortion 201 9.5.2 RF Digital Predistortion 204 9.6 The Bandwidth and Power Scalable Digital Predistortion Technique 205 9.7 Summary 206 References 207 10 Advanced Modeling and Digital Predistortion 209 10.1 Joint Quadrature Impairment and Nonlinear Distortion Compensation Using Multi-Input DPD 209 10.1.1 Modeling of Quadrature Modulator Imperfections 210 10.1.2 Dual-Input Polynomial Model for Memoryless Joint Modeling of Quadrature Imbalance and PA Distortions 211 10.1.3 Dual-Input Memory Polynomial for Joint Modeling of Quadrature Imbalance and PA Distortions Including Memory Effects 212 10.1.4 Dual-Branch Parallel Hammerstein Model for Joint Modeling of Quadrature Imbalance and PA Distortions with Memory 213 10.1.5 Dual-Conjugate-Input Memory Polynomial for Joint Modeling of Quadrature Imbalance and PA Distortions Including Memory Effects 216 10.2 Modeling and Linearization of Nonlinear MIMO Systems 216 10.2.1 Impairments in MIMO Systems 216 10.2.2 Crossover Polynomial Model for MIMO Transmitters 221 10.2.3 Dual-Input Nonlinear Polynomial Model for MIMO Transmitters 222 10.2.4 MIMO Transmitters Nonlinear Multi-Variable Polynomial Model 223 10.3 Modeling and Linearization of Dual-Band Transmitters 227 10.3.1 Generalization of the Polynomial Model to the Dual-Band Case 228 10.3.2 Two-Dimensional (2-D) Memory Polynomial Model for Dual-Band Transmitters 230 10.3.3 Phase-Aligned Multi-band Volterra DPD 231 10.4 Application of MIMO and Dual-Band Models in Digital Predistortion 235 10.4.1 Linearization of MIMO Systems with Nonlinear Crosstalk 236 10.4.2 Linearization of Concurrent Dual-Band Transmitters Using a 2-D Memory Polynomial Model 238 10.4.3 Linearization of Concurrent Tri-Band Transmitters Using 3-D Phase-Aligned Volterra Model 240 References 242 Index 247

Read more less

Book SynopsisWireless Communications Systems Design provides the basic knowledge and methodology for wireless communications design. The book mainly focuses on a broadband wireless communication system based on OFDM/OFDMA system because it is widely used in the modern wireless communication system.Table of ContentsPreface xi List of Abbreviations xiii Part I Wireless Communications Theory 1 1 Historical Sketch of Wireless Communications 3 1.1 Advancement of Wireless Communications Technologies 3 1.2 Wireless Communications, Lifestyles, and Economics 6 References 9 2 Probability Theory 11 2.1 Random Signals 11 2.2 Spectral Density 16 2.3 Correlation Functions 18 2.4 Central Limit Theorem 25 2.5 Problems 28 Reference 30 3 Wireless Channels 31 3.1 Additive White Gaussian Noise 31 3.2 Large]Scale Path Loss Models 34 3.3 Multipath Channels 38 3.4 Empirical Wireless Channel Models 46 3.5 Problems 48 References 50 4 Optimum Receiver 51 4.1 Decision Theory 51 4.2 Optimum Receiver for AWGN 55 4.3 Matched Filter Receiver 66 4.4 Coherent and Noncoherent Detection 69 4.5 Problems 73 References 74 5 Wireless Channel Impairment Mitigation Techniques 75 5.1 Diversity Techniques 75 5.2 Error Control Coding 82 5.2.1 Linear Block Codes 84 5.2.2 Convolutional Codes 92 5.3 MIMO 99 5.4 Equalization 107 5.5 OFDM 114 5.6 Problems 120 References 121 Part II Wireless Communications Blocks Design 123 6 Error Correction Codes 125 6.1 Turbo Codes 125 6.1.1 Turbo Encoding and Decoding Algorithm 125 6.1.2 Example of Turbo Encoding and Decoding 133 6.1.3 Hardware Implementation of Turbo Encoding and Decoding 149 6.2 Turbo Product Codes 155 6.2.1 Turbo Product Encoding and Decoding Algorithm 155 6.2.2 Example of Turbo Product Encoding and Decoding 156 6.2.3 Hardware Implementation of Turbo Product Encoding and Decoding 174 6.3 Low]Density Parity Check Codes 175 6.3.1 LDPC Encoding and Decoding Algorithms 175 6.3.2 Example of LDPC Encoding and Decoding 191 6.3.3 Hardware Implementation of LDPC Encoding and Decoding 199 6.4 Problems 205 References 206 7 Orthogonal Frequency]Division Multiplexing 209 7.1 OFDM System Design 209 7.2 FFT Design 217 7.3 Hardware Implementations of FFT 232 7.4 Problems 237 References 238 8 Multiple Input Multiple Output 239 8.1 MIMO Antenna Design 239 8.2 Space Time Coding 240 8.3 Example of STTC Encoding and Decoding 254 8.4 Spatial Multiplexing and MIMO Detection Algorithms 266 8.5 Problems 276 References 277 9 Channel Estimation and Equalization 279 9.1 Channel Estimation 279 9.2 Channel Estimation for MIMO–OFDM System 293 9.3 Equalization 295 9.4 Hardware Implementation of Channel Estimation and Equalizer for OFDM System 298 9.5 Problems 298 References 299 10 Synchronization 301 10.1 Fundamental Synchronization Techniques for OFDM System 301 10.2 Synchronization Errors 305 10.3 Synchronization Techniques for OFDM System 310 10.4 Hardware Implementation of OFDM Synchronization 319 10.5 Problems 320 References 321 Part III Wireless Communications Systems Design 323 11 Radio Planning 325 11.1 Radio Planning and Link Budget Analysis 325 11.2 Traffic Engineering 335 11.3 Problems 345 References 347 12 Wireless Communications Systems Design and Considerations 349 12.1 Wireless Communications Systems Design Flow 349 12.2 Wireless Communications Systems Design Considerations 353 12.3 Hardware and Software Codesign 370 12.4 Problems 377 References 378 13 Wireless Communications Blocks Integration 379 13.1 High Level View of Wireless Communications Systems 379 13.2 4G Physical Layer Systems 383 13.2.1 LTE 384 13.2.2 WiMAX 394 13.2.3 Comparison of LTE and WiMAX 400 13.3 SoC Design for 4G Communication System 401 13.3.1 Software Design for 4G Communication System 403 13.3.2 Hardware Design for 4G Communication System 404 13.4 Problems 409 References 410 Index 411

Read more less

Book SynopsisWith an emphasis on antennas and propagation, Radio Propagation and Adaptive Antennas investigates every aspect of wireless communication network design and function. The book delves into, among other applicable radio propagation topics, multipath phenomena, slow and fast fading, free-space propagation, and obstructed reflection and diffraction.Table of ContentsPreface vii Part I Fundamentals of Wireless Links and Networks 1 Wireless Communication Links with Fading 1 2 Antenna Fundamentals 34 3 Fundamentals of Wireless Networks 54 Part II Fundamentals of Radio Propagation 4 Electromagnetic Aspects of Wave Propagation over Terrain 81 5 Terrestrial Radio Communications 117 6 Indoor Radio Propagation 179 Part III Fundamentals of Adaptive Antennas 7 Adaptive Antennas for Wireless Networks 216 8 Prediction of Signal Distribution in Space, Time, and Frequency Domains in Radio Channels for Adaptive Antenna Applications 280 9 Prediction of Operational Characteristics of Adaptive Antennas 375 Part IV Practical Aspects of Terrestrial Networks Performance: Cellular and Noncellular 10 Multipath Fading Phenomena in Terrestrial Wireless Communication Links 413 11 Cellular and Noncellular Communication Networks Design Based on Radio Propagation Phenomena 494 Part V Atmospheric and Satellite Communication Links and Networks 12 Effects of the Troposphere on Radio Propagation 536 13 Ionospheric Radio Propagation 591 14 Land–Satellite Communication Links 639 Index 677

Read more less

Book SynopsisThis book provides an insight into the key practical aspects and best practice of 4G-LTE network design, performance, and deployment Design, Deployment and Performance of 4G-LTE Networks addresses the key practical aspects and best practice of 4G networks design, performance, and deployment.Table of ContentsAuthors’ Biographies xv Preface xvii Acknowledgments xix Abbreviations and Acronyms xxi 1 LTE Network Architecture and Protocols 1 Ayman Elnashar and Mohamed A. El-saidny 1.1 Evolution of 3GPP Standards 2 1.1.1 3GPP Release 99 3 1.1.2 3GPP Release 4 3 1.1.3 3GPP Release 5 3 1.1.4 3GPP Release 6 4 1.1.5 3GPP Release 7 4 1.1.6 3GPP Release 8 5 1.1.7 3GPP Release 9 and Beyond 5 1.2 Radio Interface Techniques in 3GPP Systems 6 1.2.1 Frequency Division Multiple Access (FDMA) 6 1.2.2 Time Division Multiple Access (TDMA) 6 1.2.3 Code Division Multiple Access (CDMA) 7 1.2.4 Orthogonal Frequency Division Multiple Access (OFDMA) 7 1.3 Radio Access Mode Operations 7 1.3.1 Frequency Division Duplex (FDD) 8 1.3.2 Time Division Duplex (TDD) 8 1.4 Spectrum Allocation in UMTS and LTE 8 1.5 LTE Network Architecture 10 1.5.1 Evolved Packet System (EPS) 10 1.5.2 Evolved Packet Core (EPC) 11 1.5.3 Evolved Universal Terrestrial Radio Access Network (E-UTRAN) 13 1.5.4 LTE User Equipment 13 1.6 EPS Interfaces 14 1.6.1 S1-MME Interface 14 1.6.2 LTE-Uu Interface 15 1.6.3 S1-U Interface 17 1.6.4 S3 Interface (SGSN-MME) 18 1.6.5 S4 (SGSN to SGW) 18 1.6.6 S5/S8 Interface 19 1.6.7 S6a (Diameter) 21 1.6.8 S6b Interface (Diameter) 21 1.6.9 S6d (Diameter) 22 1.6.10 S9 Interface (H-PCRF-VPCRF) 23 1.6.11 S10 Interface (MME-MME) 23 1.6.12 S11 Interface (MME–SGW) 23 1.6.13 S12 Interface 23 1.6.14 S13 Interface 24 1.6.15 SGs Interface 24 1.6.16 SGi Interface 25 1.6.17 Gx Interface 26 1.6.18 Gy and Gz Interfaces 27 1.6.19 DNS Interface 27 1.6.20 Gn/Gp Interface 27 1.6.21 SBc Interface 28 1.6.22 Sv Interface 28 1.7 EPS Protocols and Planes 29 1.7.1 Access and Non-Access Stratum 29 1.7.2 Control Plane 29 1.7.3 User Plane 30 1.8 EPS Procedures Overview 31 1.8.1 EPS Registration and Attach Procedures 31 1.8.2 EPS Quality of Service (QoS) 34 1.8.3 EPS Security Basics 36 1.8.4 EPS Idle and Active States 38 1.8.5 EPS Network Topology for Mobility Procedures 39 1.8.6 EPS Identifiers 44 References 44 2 LTE Air Interface and Procedures 47 Mohamed A. El-saidny 2.1 LTE Protocol Stack 47 2.2 SDU and PDU 48 2.3 LTE Radio Resource Control (RRC) 50 2.4 LTE Packet Data Convergence Protocol Layer (PDCP) 52 2.4.1 PDCP Architecture 53 2.4.2 PDCP Data and Control SDUs 53 2.4.3 PDCP Header Compression 54 2.4.4 PDCP Ciphering 54 2.4.5 PDCP In-Order Delivery 54 2.4.6 PDCP in LTE versus HSPA 55 2.5 LTE Radio Link Control (RLC) 55 2.5.1 RLC Architecture 56 2.5.2 RLC Modes 57 2.5.3 Control and Data PDUs 60 2.5.4 RLC in LTE versus HSPA 60 2.6 LTE Medium Access Control (MAC) 61 2.7 LTE Physical Layer (PHY) 61 2.7.1 HSPA(+) Channel Overview 61 2.7.2 General LTE Physical Channels 71 2.7.3 LTE Downlink Physical Channels 71 2.7.4 LTE Uplink Physical Channels 72 2.8 Channel Mapping of Protocol Layers 73 2.8.1 E-UTRAN Channel Mapping 73 2.8.2 UTRAN Channel Mapping 76 2.9 LTE Air Interface 76 2.9.1 LTE Frame Structure 76 2.9.2 LTE Frequency and Time Domains Structure 76 2.9.3 OFDM Downlink Transmission Example 80 2.9.4 Downlink Scheduling 81 2.9.5 Uplink Scheduling 88 2.9.6 LTE Hybrid Automatic Repeat Request (HARQ) 89 2.10 Data Flow Illustration Across the Protocol Layers 90 2.10.1 HSDPA Data Flow 90 2.10.2 LTE Data Flow 91 2.11 LTE Air Interface Procedures 92 2.11.1 Overview 92 2.11.2 Frequency Scan and Cell Identification 92 2.11.3 Reception of Master and System Information Blocks (MIB and SIB) 93 2.11.4 Random Access Procedures (RACH) 94 2.11.5 Attach and Registration 95 2.11.6 Downlink and Uplink Data Transfer 96 2.11.7 Connected Mode Mobility 96 2.11.8 Idle Mode Mobility and Paging 99 References 100 3 Analysis and Optimization of LTE System Performance 103 Mohamed A. El-saidny 3.1 Deployment Optimization Processes 104 3.1.1 Profiling Device and User Behavior in the Network 105 3.1.2 Network Deployment Optimization Processes 107 3.1.3 Measuring the Performance Targets 108 3.1.4 LTE Troubleshooting Guidelines 119 3.2 LTE Performance Analysis Based on Field Measurements 123 3.2.1 Performance Evaluation of Downlink Throughput 127 3.2.2 Performance Evaluation of Uplink Throughput 131 3.3 LTE Case Studies and Troubleshooting 134 3.3.1 Network Scheduler Implementations 135 3.3.2 LTE Downlink Throughput Case Study and Troubleshooting 136 3.3.3 LTE Uplink Throughput Case Studies and Troubleshooting 139 3.3.4 LTE Handover Case Studies 146 3.4 LTE Inter-RAT Cell Reselection 153 3.4.1 Introduction to Cell Reselection 155 3.4.2 LTE to WCDMA Inter-RAT Cell Reselection 155 3.4.3 WCDMA to LTE Inter-RAT Cell Reselection 160 3.5 Inter-RAT Cell Reselection Optimization Considerations 165 3.5.1 SIB-19 Planning Strategy for UTRAN to E-UTRAN Cell Reselection 165 3.5.2 SIB-6 Planning Strategy for E-UTRAN to UTRAN Cell Reselection 167 3.5.3 Inter-RAT Case Studies from Field Test 168 3.5.4 Parameter Setting Trade-off 174 3.6 LTE to LTE Inter-frequency Cell Reselection 177 3.6.1 LTE Inter-Frequency Cell Reselection Rules 177 3.6.2 LTE Inter-Frequency Optimization Considerations 177 3.7 LTE Inter-RAT and Inter-frequency Handover 180 3.7.1 Inter-RAT and Inter-Frequency Handover Rules 187 3.7.2 Inter-RAT and Inter-Frequency Handover Optimization Considerations 188 References 189 4 Performance Analysis and Optimization of LTE Key Features: C-DRX, CSFB, and MIMO 191 Mohamed A. El-saidny and Ayman Elnashar 4.1 LTE Connected Mode Discontinuous Reception (C-DRX) 192 4.1.1 Concepts of DRX for Battery Saving 193 4.1.2 Optimizing C-DRX Performance 195 4.2 Circuit Switch Fallback (CSFB) for LTE Voice Calls 204 4.2.1 CSFB to UTRAN Call Flow and Signaling 206 4.2.2 CSFB to UTRAN Features and Roadmap 216 4.2.3 Optimizing CSFB to UTRAN 231 4.3 Multiple-Input, Multiple-Output (MIMO) Techniques 252 4.3.1 Introduction to MIMO Concepts 252 4.3.2 3GPP MIMO Evolution 256 4.3.3 MIMO in LTE 258 4.3.4 Closed-Loop MIMO (TM4) versus Open-Loop MIMO (TM3) 261 4.3.5 MIMO Optimization Case Study 267 References 270 5 Deployment Strategy of LTE Network 273 Ayman Elnashar 5.1 Summary and Objective 273 5.2 LTE Network Topology 273 5.3 Core Network Domain 276 5.3.1 Policy Charging and Charging (PCC) Entities 280 5.3.2 Mobility Management Entity (MME) 283 5.3.3 Serving Gateway (SGW) 286 5.3.4 PDN Gateway (PGW) 287 5.3.5 Interworking with PDN (DHCP) 289 5.3.6 Usage of RADIUS on the Gi/SGi Interface 291 5.3.7 IPv6 EPC Transition Strategy 293 5.4 IPSec Gateway (IPSec GW) 294 5.4.1 IPSec GW Deployment Strategy and Redundancy Options 299 5.5 EPC Deployment and Evolution Strategy 300 5.6 Access Network Domain 303 5.6.1 E-UTRAN Overall Description 303 5.6.2 Home eNB 305 5.6.3 Relaying 307 5.6.4 End-to-End Routing of the eNB 308 5.6.5 Macro Sites Deployment Strategy 312 5.6.6 IBS Deployment Strategy 317 5.6.7 Passive Inter Modulation (PIM) 319 5.7 Spectrum Options and Guard Band 327 5.7.1 Guard Band Requirement 327 5.7.2 Spectrum Options for LTE 327 5.8 LTE Business Case and Financial Analysis 333 5.8.1 Key Financial KPIs [31] 334 5.9 Case Study: Inter-Operator Deployment Scenario 341 References 347 6 Coverage and Capacity Planning of 4G Networks 349 Ayman Elnashar 6.1 Summary and Objectives 349 6.2 LTE Network Planning and Rollout Phases 349 6.3 LTE System Foundation 351 6.3.1 LTE FDD Frame Structure 351 6.3.2 Slot Structure and Physical Resources 353 6.3.3 Reference Signal Structure 356 6.4 PCI and TA Planning 360 6.4.1 PCI Planning Introduction 360 6.4.2 PCI Planning Guidelines 361 6.4.3 Tracking Areas (TA) Planning 362 6.5 PRACH Planning 370 6.5.1 Zadoff-Chu Sequence 371 6.5.2 PRACH Planning Procedures 372 6.5.3 Practical PRACH Planning Scenarios 373 6.6 Coverage Planning 375 6.6.1 RSSI, RSRP, RSRQ, and SINR 375 6.6.2 The Channel Quality Indicator 378 6.6.3 Modulation and Coding Scheme and Link Adaptation 381 6.6.4 LTE Link Budget and Coverage Analysis 385 6.6.5 Comparative Analysis with HSPA+ 401 6.6.6 Link Budget for LTE Channels 405 6.6.7 RF Propagation Models and Model Tuning 409 6.7 LTE Throughput and Capacity Analysis 418 6.7.1 Served Physical Layer Throughput Calculation 418 6.7.2 Average Spectrum Efficiency Estimation 418 6.7.3 Average Sector Capacity 419 6.7.4 Capacity Dimensioning Process 419 6.7.5 Capacity Dimensioning Exercises 423 6.7.6 Calculation of VoIP Capacity in LTE 426 6.7.7 LTE Channels Planning 431 6.8 Case Study: LTE FDD versus LTE TDD 437 References 443 7 Voice Evolution in 4G Networks 445 Mahmoud R. Sherif 7.1 Voice over IP Basics 445 7.1.1 VoIP Protocol Stack 445 7.1.2 VoIP Signaling (Call Setup) 449 7.1.3 VoIP Bearer Traffic (Encoded Speech) 449 7.2 Voice Options for LTE 451 7.2.1 SRVCC and CSFB 451 7.2.2 Circuit Switched Fallback (CSFB) 452 7.3 IMS Single Radio Voice Call Continuity (SRVCC) 455 7.3.1 IMS Overview 456 7.3.2 VoLTE Call Flow and Interaction with IMS 460 7.3.3 Voice Call Continuity Overview 469 7.3.4 SRVCC from VoLTE to 3G/2G 471 7.3.5 Enhanced SRVCC (eSRVCC) 480 7.4 Key VoLTE Features 482 7.4.1 End-to-End QoS Support 482 7.4.2 Semi-Persistent Scheduler 486 7.4.3 TTI Bundling 488 7.4.4 Connected Mode DRX 491 7.4.5 Robust Header Compression (ROHC) 492 7.4.6 VoLTE Vocoders and De-Jitter Buffer 497 7.5 Deployment Considerations for VoLTE 503 References 505 8 4G Advanced Features and Roadmap Evolutions from LTE to LTE-A 507 Ayman Elnashar and Mohamed A. El-saidny 8.1 Performance Comparison between LTE’s UE Category 3 and 4 509 8.1.1 Trial Overview 512 8.1.2 Downlink Performance Comparison in Near and Far Cell Conditions 513 8.1.3 Downlink Performance Comparison in Mobility Conditions 515 8.2 Carrier Aggregation 516 8.2.1 Basic Definitions of LTE Carrier Aggregation 518 8.2.2 Band Types of LTE Carrier Aggregation 519 8.2.3 Impact of LTE Carrier Aggregation on Protocol Layers 520 8.3 Enhanced MIMO 520 8.3.1 Enhanced Downlink MIMO 522 8.3.2 Uplink MIMO 523 8.4 Heterogeneous Network (HetNet) and Small Cells 523 8.4.1 Wireless Backhauling Applicable to HetNet Deployment 524 8.4.2 Key Features for HetNet Deployment 528 8.5 Inter-Cell Interference Coordination (ICIC) 529 8.6 Coordinated Multi-Point Transmission and Reception 531 8.6.1 DL CoMP Categories 531 8.6.2 UL CoMP Categories 533 8.6.3 Performance Evaluation of CoMP 533 8.7 Self-Organizing, Self-Optimizing Networks (SON) 535 8.7.1 Automatic Neighbor Relation (ANR) 536 8.7.2 Mobility Robust Optimization (MRO) 537 8.7.3 Mobility Load Balancing (MLB) 539 8.7.4 SON Enhancements in LTE-A 540 8.8 LTE-A Relays and Home eNodeBs (HeNB) 540 8.9 UE Positioning and Location-Based Services in LTE 541 8.9.1 LBS Overview 541 8.9.2 LTE Positioning Architecture 543 References 544 Index 547

Read more less

Book SynopsisThis extensively updated second edition of LTE Signaling, Troubleshooting and Performance Measurement describes the LTE signaling protocols and procedures for the third generation of mobile communications and beyond. It is one of the few books available that explain the LTE signaling messages, procedures and measurements down to the bit & byte level, and all trace examples are taken for a real lab and field trial traces. This book covers the crucial key performance indicators (KPI) to be measured during field trials and deployment phase of new LTE networks. It describes how statistic values can be aggregated and evaluated, and how the network can be optimized during the first stages of deployment, using dedicated examples to enhance understanding. Written by experts in the field of mobile communications, this book systematically describes the most recent LTE signaling procedures, explaining how to identify and troubleshoot abnormal network behavior and common failure cTable of ContentsForeword xi Acknowledgements xiii 1 Standards, Protocols, and Functions 1 1.1 LTE Standards and Standard Roadmap 2 1.2 LTE Radio Access Network Architecture 9 1.3 Network Elements and Functions 10 1.3.1 The eNodeB (eNB) 11 1.3.2 Mobility Management Entity (MME) 12 1.3.3 Serving Gateway (S-GW) 12 1.3.4 Packet Data Network Gateway (PDN-GW) 13 1.3.5 Interfaces and Reference Points 13 1.4 Area and Subscriber Identities 18 1.4.1 Domains and Strati 18 1.4.2 IMSI 19 1.4.3 LMSI, TMSI, P-TMSI, M-TMSI, and S-TMSI 20 1.4.4 GUTI 21 1.4.5 IMEI 22 1.4.6 RNTI 22 1.4.7 Location Area, Routing Area, Service Area, Tracking Area, and Cell Global Identity 24 1.4.8 Mapping between Temporary and Area Identities for EUTRAN and UTRAN/GERAN-Based Systems 25 1.4.9 GSM Base Station Identification 27 1.4.10 UTRA Base Station Identification 28 1.4.11 Numbering, Addressing, and Identification in the Session Initiation Protocol 29 1.4.12 Access Point Name 30 1.5 User Equipment 30 1.5.1 UE Categories 31 1.6 QoS Architecture 32 1.7 LTE Security 34 1.8 Radio Interface Basics 38 1.8.1 Duplex Methods 40 1.8.2 Multiple Access Methods 42 1.8.3 OFDM Principles and Modulation 46 1.8.4 Multiple Access in OFDM–OFDMA 48 1.8.5 Resource Blocks 49 1.8.6 Downlink Slot Structure 53 1.8.7 OFDM Scheduling on LTE DL 56 1.8.8 SC-FDMA Principles and Modulation 60 1.8.9 Scheduling on LTE UL 62 1.8.10 Uplink Slot Structure 64 1.8.11 Link Adaptation in LTE 64 1.8.12 Physical Channels in LTE 70 1.8.13 Transport Channels in LTE 79 1.8.14 Channel Mapping and Multiplexing 80 1.8.15 Initial UE Radio Access 82 1.8.16 UE Random Access 82 1.9 Hybrid ARQ 87 1.9.1 Synchronous HARQ in LTE Uplink 90 1.9.2 Asynchronous HARQ in LTE Downlink 91 1.9.3 HARQ Example 92 1.10 LTE Advanced 94 1.10.1 Increasing Spectral Efficiency 95 1.10.2 Carrier Aggregation 95 1.10.3 Heterogeneous Networks 95 1.10.4 Inter-Cell Interference Coordination 97 1.11 LTE Network Protocol Architecture 98 1.11.1 Uu–Control/User Plane 98 1.11.2 S1–Control/User Plane 99 1.11.3 X2–User/Control Plane 100 1.11.4 S6a–Control Plane 100 1.11.5 S3/S4/S5/S8/S10/S11–Control Plane/User Plane 101 1.12 Protocol Functions, Encoding, Basic Messages, and Information Elements 102 1.12.1 Ethernet 102 1.12.2 Internet Protocol (IPv4/IPv6) 102 1.12.3 Stream Control Transmission Protocol (SCTP) 106 1.12.4 Radio Interface Layer 2 Protocols 108 1.12.5 Medium Access Control (MAC) Protocol 110 1.12.6 Radio Link Control (RLC) Protocol 111 1.12.7 Packet Data Convergence Protocol (PDCP) 115 1.12.8 Radio Resource Control (RRC) Protocol 117 1.12.9 Non-Access Stratum (NAS) Protocol 124 1.12.10 S1 Application Part (S1AP) 124 1.12.11 User Datagram Protocol (UDP) 128 1.12.12 GPRS Tunneling Protocol (GTP) 129 1.12.13 Transmission Control Protocol (TCP) 136 1.12.14 Session Initiation Protocol (SIP) 138 1.12.15 DIAMETER on EPC Interfaces 139 2 E-UTRAN/EPC Signaling 145 2.1 S1 Setup 145 2.1.1 S1 Setup: Message Flow 145 2.1.2 S1 Setup: Failure Analysis 147 2.2 Initial Attach 149 2.2.1 Procedure 150 2.3 UE Context Release Requested by eNodeB 166 2.3.1 Procedure 166 2.4 UE Service Request 168 2.4.1 Procedure 169 2.5 Dedicated Bearer Setup 172 2.6 Inter-eNodeB Handover over X2 174 2.6.1 Procedure 176 2.7 S1 Handover 186 2.7.1 Procedure 188 2.8 Dedicated Bearer Release 199 2.9 Detach 200 2.9.1 Procedure 200 2.10 Failure Cases in E-UTRAN and EPC 203 2.11 Voice over LTE (SIP) Call–Complete Scenario 203 2.12 Inter-RAT Cell Reselection 4G-3G-4G 210 2.13 Normal/Periodical Tracking Area Update 211 2.14 CS Fallback End-to-End S1/IuCS/IuPS 212 2.15 Paging 213 2.16 Multi-E-RAB Call Scenarios 214 2.16.1 Multi-E-RAB Call Scenarios without Subscriber Mobility 214 2.16.2 Multi-E-RAB Call with Intra-LTE Handover 215 2.16.3 Inter-RAT Mobility of a Multi-E-RAB Call Using CS Fallback 216 2.16.4 Abnormal Releases of Calls with VoLTE Services 217 3 Radio Interface Signaling Procedures 219 3.1 RRC Connection Setup, Attach, and Default Bearer Setup 220 3.1.1 Random Access and RRC Connection Setup Procedure 220 3.1.2 RRC Connection Reconfiguration and Default Bearer Setup 229 3.1.3 RRC Connection Release 238 3.2 LTE Mobility 238 3.2.1 Intra-eNB Intra-Frequency HO 242 3.2.2 Intra-eNodeB Inter-Frequency Handover 243 3.2.3 Inter-eNodeB Intra-Frequency Handover 248 3.2.4 Inter-RAT Handover to 3G 253 3.2.5 Inter-RAT Handover to 2G 255 3.2.6 Inter-RAT Blind Redirection to 3G 257 3.2.7 Inter-RAT Blind Redirection to 2G 259 3.2.8 CS Fallback 260 3.3 Failure Cases 262 4 Key Performance Indicators and Measurements for LTE Radio Network Optimization 267 4.1 Monitoring Solutions for LTE Interfaces 267 4.1.1 Monitoring the Air Interface (Uu) 267 4.1.2 Antenna-Based Monitoring 269 4.1.3 Coax-Based Monitoring 270 4.1.4 CPRI-Based Monitoring 270 4.1.5 Monitoring the E-UTRAN Line Interface 272 4.1.6 Monitoring the eNodeB Trace Port 276 4.2 Monitoring the Scheduler Efficiency 279 4.2.1 UL and DL Scheduling Resources 285 4.2.2 X2 Load Indication 286 4.2.3 The eNodeB Layer 2 Measurements 288 4.3 Radio Quality Measurements 290 4.3.1 UE Measurements 293 4.3.2 The eNodeB Physical Layer Measurements 297 4.3.3 Radio Interface Tester Measurements 301 4.3.4 I/Q Constellation Diagrams 302 4.3.5 EVM/Modulation Error Ratio 304 4.4 Control Plane Performance Counters and Delay Measurements 306 4.4.1 Network Accessibility 307 4.4.2 Network Retainability 316 4.4.3 Mobility (Handover) 318 4.5 User Plane KPIs 322 4.5.1 IP Throughput 323 4.5.2 Application Throughput 325 4.5.3 TCP Startup KPIs 327 4.5.4 TCP Round-Trip Time 328 4.5.5 Packet Jitter 329 4.5.6 Packet Delay and Packet Loss on a Hop-to-Hop Basis 330 4.6 KPI Visualization using Geographical Maps (Geolocation) 331 4.6.1 The Minimize Drive Test Feature Set of 3GPP 333 Acronyms 337 Bibliography 343 Index 345

Read more less

Book SynopsisDetails the paradigms of opportunistic spectrum sharing and white space access as effective means to satisfy increasing demand for high-speed wireless communication and for novel wireless communication applications This book addresses opportunistic spectrum sharing and white space access, being particularly mindful of practical considerations and solutions. In Part I, spectrum sharing implementation issues are considered in terms of hardware platforms and software architectures for realization of flexible and spectrally agile transceivers. Part II addresses practical mechanisms supporting spectrum sharing, including spectrum sensing for opportunistic spectrum access, machine learning and decision making capabilities, aggregation of spectrum opportunities, and spectrally-agile radio waveforms. Part III presents the ongoing work on policy and regulation for efficient and reliable spectrum sharing, including major recent steps forward in TV White Space (TTable of ContentsLIST OF CONTRIBUTORS xi INTRODUCTION xvOliver Holland, Hanna Bogucka, and Arturas Medeisis ACRONYMS xxiii PART I FLEXIBLE RADIO HARDWARE AND SOFTWARE PLATFORMS SUPPORTING SPECTRUM SHARING 1 1 The Universal Software Radio Peripheral (USRP) Family of Low-Cost SDRs 3Matt Ettus and Martin Braun 2 On the GNU Radio Ecosystem 25Thomas W. Rondeau 3 Wireless Open-Access Research Platform (WARP) for Flexible Radio 49Junaid Ansari and Petri Mähönen 4 A Dynamically Reconfigurable Software Radio Framework: Iris 81Paul Sutton 5 OpenAirInterface and ExpressMIMO2 for Spectrally Agile Communication 99Bassem Zayen, Florian Kaltenberger, and Raymond Knopp 6 CORAL Cognitive WiFi Networking System: Case Studies of Rural Applications in India 123John Sydor PART II PRACTICAL MECHANISMS SUPPORTING SPECTRUM SHARING 141 7 Cooperative Sensing of Spectrum Opportunities 143Giuseppe Caso, Luca De Nardis, Ragnar Thobaben, and Maria-Gabriella Di Benedetto 8 A Machine-Learning Approach Based on Bio-Inspired Intelligence 167Dimitrios Karvounas, Aimilia Bantouna, Andreas Georgakopoulos, Kostas Tsagkaris, Vera Stavroulaki, and Panagiotis Demestichas 9 Spectrally Agile Waveforms 191Alexander M. Wyglinski, Adrian Kliks, Pawel Kryszkiewicz, Amit P. Sail, and Hanna Bogucka 10 Aggregation of Spectrum Opportunities 221Florian Kaltenberger, Theodoros A. Tsiftsis, Fotis Foukalas, Shuyu Ping, and Oliver Holland 11 Policies for Efficient Spectrum Sharing 239Liljana Gavrilovska, Vladimir Atanasovski, and Gianmarco Baldini PARTIII REGULATORY SOLUTIONS FOR SPECTRUM SHARING 257 12 International Regulatory Framework for Spectrum and Spectrum Sharing 259Peter Anker 13 Regulations for Spectrum Sharing in the USA 277Lee Pucker 14 UK Framework for Access to TV White Spaces 313Hamid Reza Karimi 15 Spectrum Sharing Using Geo-Location Databases 339Jeffrey C. Schmidt and Peter Stanforth 16 Novel Licensing Schemes 369Oliver Holland, Arturo Basaure, and Wataru Yamada PARTIV SPECTRUM SHARING BUSINESS SCENARIOS AND ECONOMIC CONSIDERATIONS 391 17 Economic and Game Theoretic Models for Spectrum Sharing 393Hamed Ahmadi, Irene Macaluso, Zaheer Khan, Hanna Bogucka, and Luiz A. DaSilva 18 Business Benefits of Licensed Shared Access (LSA) for Key Stakeholders 407Marja Matinmikko, Hanna Okkonen, Seppo Yrjölä, Petri Ahokangas, Miia Mustonen, Marko Palola, Vânia Gonçalves, Anri Kivimäki, Esko Luttinen, and Jukka Kemppainen 19 Initial Standardization of Disruptive Innovations in Radiocommunication Technology in Consortia 425Dirk-Oliver von der Emden 20 Spectrum as a Platform: a Critical Assessment of the Value Promise of Spectrum Sharing Solutions 453Olivier Rits, Simon Delaere, and Pieter Ballon PART V SPECTRUM SHARING DEPLOYMENT SCENARIOS IN PRACTICE 479 21 TV White Spaces with Geo-Location Database Access: Practical Considerations and Trials in Europe 481Rogério Dionísio, José Ribeiro, Jorge Ribeiro, Paulo Marques, and Jonathan Rodriguez 22 Developments and Practical Field Trials of TVWS Technologies 513Kentaro Ishizu, Keiichi Mizutani, Takeshi Matsumura, Ha-Nguyen Tran, Stanislav Filin, Hirokazu Sawada, and Hiroshi Harada 23 Cognitive Wireless Regional Area Network Standard 551Apurva Mody, Gerald Chouinard, Stephen J. Shellhammer, Monisha Ghosh, and Dave Cavalcanti 24 ETSI Opportunistic Spectrum Sharing Technology for (TV) White Spaces 605Markus Dominik Mueck, Naotaka Sato, Chen Sun, Martino Freda, Pekka Ojanen, Dong Zhou, Junfeng Xiao, Rogério Pais Dionisio, and Paulo Marques 25 The IEEE Dynamic Spectrum Access Networks Standards Committee (DySPAN-SC) and IEEE 1900 Working Groups 631Oliver Holland, Hiroshi Harada, Ha-Nguyen Tran, Bernd Bochow, Masayuki Ariyoshi, Matthew Sherman, Michael Gundlach, Stanislav Filin, and Adrian Kliks 26 Spectrum to Unlash Machine-to-Machine Uptake 649Mischa Dohler and Yue Gao CONCLUSIONS AND FUTURE WORK 679Oliver Holland, Hanna Bogucka, and Arturas Medeisis INDEX 689

Read more less

Book SynopsisThis book brings together a group of visionaries and technical experts from academia to industry to discuss the applications and technologies that will comprise the next set of cellular advancements (5G).Table of ContentsList of Contributors xv List of Acronyms xix About the Companion Website xxxi Part I Overview of 5G 1 1 Introduction 3 Shilpa Talwar and Rath Vannithamby 1.1 Evolution of Cellular Systems through the Generations 3 1.2 Moving Towards 5G 4 1.3 5G Networks and Devices 5 1.4 Outline of the Book 7 References 8 2 5G Requirements 9 Anass Benjebbour, Yoshihisa Kishiyama, and Takehiro Nakamura 2.1 Introduction 9 2.2 Emerging Trends in Mobile Applications and Services 10 2.3 General Requirements 15 References 21 3 Collaborative 5G Research within the EU Framework of Funded Research 23 Michael Faerber 3.1 Rationale for 5G Research and the EU’s Motivation 23 3.2 EU Research 25 References 33 4 5G: Transforming the User Wireless Experience 34 David Ott, Nageen Himayat, and Shilpa Talwar 4.1 Introduction 34 4.2 Intel’s Vision of 5G Technologies 34 4.3 Intel Strategic Research Alliance on 5G 40 4.4 ISRA 5G Technical Objectives and Goals 40 4.5 ISRA 5G Project Summaries 42 References 50 Part II Candidate Technologies – Evolutionary 53 5 Towards Green and Soft 55 Chih‐Lin I and Shuangfeng Han 5.1 Chapter Overview 55 5.2 Efforts on Green and Soft 5G Networks 56 5.3 Rethink Shannon: EE and SE Co‐design for a Green Network 57 5.4 “No More Cell” for a Green and Soft Network 67 5.5 Summary 75 Acknowledgments 76 References 76 6 Proactive Caching in 5G Small Cell Networks 78 Ejder Baştuğ, Mehdi Bennis, and Mérouane Debbah 6.1 Small Cell Networks: Past, Present and Future Trends 78 6.2 Cache‐enabled Proactive Small Cell Networks 80 6.3 System Model 81 6.4 Proactive Caching at Base Stations 82 6.5 Proactive Caching at User Terminals 85 6.6 Related Work and Research Directions 90 6.7 Conclusions 95 Acknowledgments 95 References 95 7 Modeling Multi‐Radio Coordination and Integration in Converged Heterogeneous Networks 99 Olga Galinina, Sergey Andreev, Alexander Pyattaev, Mikhail Gerasimenko, Yevgeni Koucheryavy, Nageen Himayat, Kerstin Johnsson, and Shu‐ping Yeh 7.1 Enabling Technologies for Multi‐Radio Heterogeneous Networks 99 7.2 Comprehensive Methodology for Space‐Time Network Analysis 105 7.3 Analysis of Random Dynamic HetNets 114 7.4 Quantifying Performance with System‐level Evaluations 121 7.5 Summary and Conclusions 126 Acknowledgments 126 References 126 8 Distributed Resource Allocation in 5G Cellular Networks 129 Monowar Hasan and Ekram Hossain 8.1 Introduction 129 8.2 Multi‐tier 5G Cellular: Overview and Challenges 132 8.3 System Model 135 8.4 Resource Allocation using Stable Matching 139 8.5 Message‐passing Approach for Resource Allocation 143 8.6 Auction‐based Resource Allocation 151 8.7 Qualitative Comparison of the Resource Allocation Schemes 157 8.8 Summary and Conclusion 157 References 159 Additional Reading 160 9 Device‐to‐Device Communications 162 Andreas F. Molisch, Mingyue Ji, Joongheon Kim, Daoud Burghal, and Arash Saber Tehrani 9.1 Introduction and Motivation 162 9.2 Propagation Channels 163 9.3 Neighbor Discovery and Channel Estimation 166 9.4 Mode Selection and Resource Allocation 170 9.5 Scheduling 175 9.6 Multi‐hop D2D 180 9.7 Standardization 183 9.8 Applications 184 9.9 D2D for Video 186 9.10 Conclusions 191 Acknowledgments 191 References 191 10 Energy‐efficient Wireless OFDMA Networks 199 Cong Xiong and Geoffrey Ye Li 10.1 Overview 199 10.2 Energy Efficiency and Energy‐efficient Wireless Networks 200 10.3 Energy Efficiency and Spectral Efficiency Tradeoff in OFDMA 201 10.4 Energy Efficiency, Power, and Delay Tradeoff in OFDMA 208 10.5 Energy‐efficient Resource Allocation for Downlink OFDMA 212 10.6 Energy‐efficient Resource Allocation for Uplink OFDMA 217 10.7 Concluding Remarks 219 References 220 11 Advanced Multiple‐access and MIMO Techniques 222 NOMA sections Anass Benjebbour, Anxin Li, Kazuaki Takeda, Yoshihisa Kishiyama, and Takehiro Nakamura SV‐MIMO sections Yuki Inoue, Yoshihisa Kishiyama, and Takehiro Nakamura 11.1 Introduction 222 11.2 Non‐orthogonal Multiple Access 225 11.3 Smart Vertical MIMO 238 11.4 Conclusion 247 References 248 12 M2M Communications 250 Rapeepat Ratasuk, Amitava Ghosh, and Benny Vejlgaard 12.1 Chapter Overview 250 12.2 M2M Communications 250 12.3 LTE Evolution for M2M 253 12.4 5G for M2M Communications 270 12.5 Conclusion 273 References 274 13 Low‐latency Radio‐interface Perspectives for Small‐cell 5G Networks 275 Toni Levanen, Juho Pirskanen, and Mikko Valkama 13.1 Introduction to Low‐latency Radio‐interface Design 275 13.2 Small‐cell Channel Environment Considerations and Expected Traffic 277 13.3 New Radio‐interface Design for Low‐latency 5G Wireless Access 283 13.4 Extending the 5GETLA Reference Design to Millimeter‐Wave Communications 296 13.5 Conclusions and Open Research Topics 299 Part III Candidate Technologies – Revolutionary 303 14 New Physical‐layer Waveforms for 5G 305 Gerhard Wunder, Martin Kasparick, Peter Jung, Thorsten Wild, Frank Schaich, Yejian Chen, Gerhard Fettweis, Ivan Gaspar, Nicola Michailow, Maximilian Matthé, Luciano Mendes, Dimitri Kténas, Jean‐Baptiste Doré, Vincent Berg, Nicolas Cassiau, Slawomir Pietrzyk, and Mateusz Buczkowski 14.1 Why OFDM Fails 305 14.2 Unified Frame Structure 308 14.3 Waveform Candidates and Multiple‐access Approaches 310 14.4 One‐shot Random Access 328 14.5 Conclusions 339 References 339 15 Massive MIMO Communications 342 Frederick W. Vook, Amitava Ghosh, and Timothy A. Thomas 15.1 Introduction 342 15.2 Overview of Multi‐Antenna Techniques in LTE 343 15.3 Moving to 5G Cellular with Large‐scale Antenna Arrays 345 15.4 Antenna‐array Architectures for 5G Cellular 348 15.5 Massive MIMO for Evolved LTE Systems (Below 6 GHz) 349 15.6 Massive MIMO for cmWave and mmWave Systems (Above 6 GHz) 358 15.7 Conclusion 362 References 363 16 Full‐duplex Radios 365 Dinesh Bharadia and Sachin Katti 16.1 The Problem 367 16.2 Our Design 372 16.3 Implementation 381 16.4 Evaluation 383 16.5 Discussion and Conclusion 393 References 393 17 Point to Multi‐point, In‐band mmWave Backhaul for 5G Networks 395 Rakesh Taori and Arun Sridharan 17.1 Introduction 395 17.2 Feasibility of In‐band Backhaul 397 17.3 Deployment Assumptions 400 17.4 In‐band Backhaul Design Considerations 402 17.5 TDM‐based Scheduling Scheme for In‐band Backhauling 403 17.6 Concluding Remarks 407 Acknowledgments 407 References 407 18 Application of NFV and SDN to 5G Infrastructure 408 Ashok Sunder Rajan and Kannan Babu Ramia 18.1 Chapter Overview 408 18.2 Background 408 18.3 NFV and SDN 409 18.4 Network Planning and Engineering 410 18.5 Cellular Wireless Network Infrastructure 414 18.6 Network Workloads and Capacity Factors 417 18.7 Conclusion 419 References 420 Index 421

Read more less

Book SynopsisThe essential guide to state-of-the art mobile positioning and tracking techniquesfully updated for new and emerging trends in the field Mobile Positioning and Tracking, Second Edition explores state-of-the-art mobile positioning solutions applied on top of current wireless communication networks. Application areas covered include positioning, data fusion and filtering, tracking, error mitigation, both conventional and cooperative positioning technologies and systems, and more. The authors fill the gap between positioning and communication systems, showing how features of wireless communications systems can be used for positioning purposes and how the retrieved location information can be used to enhance the performance of wireless networks. Unlike other books on the subject, Mobile Positioning and Tracking: From Conventional to Cooperative Techniques, 2nd Edition covers the entire positioning and tracking value chain, starting from the measurementTable of ContentsAbout the Authors xv List of Contributors xvii Preface xix Acknowledgements xxi List of Abbreviations xxiii Notations xxxi 1 Introduction 1Joaõ Figueiras, Francescantonio Della Rosa and Simone Frattasi 1.1 Application Areas of Positioning (Chapter 2) 5 1.2 Basics of Wireless Communications for Positioning (Chapter 3) 5 1.3 Fundamentals of Positioning (Chapter 4) 5 1.4 Data Fusion and Filtering Techniques (Chapter 5) 6 1.5 Fundamentals of Tracking (Chapter 6) 6 1.6 Error Mitigation Techniques (Chapter 7) 7 1.7 Positioning Systems and Technologies (Chapter 8) 7 1.8 Ultrawideband Positioning and Tracking (Chapter 9) 8 1.9 Indoor Positioning in WLAN (Chapter 10) 8 1.10 Cooperative Multi-tag Localization in RFID Systems (Chapter 11) 9 1.11 Cooperative Mobile Positioning (Chapter 12) 9 2 Application Areas of Positioning 11Simone Frattasi 2.1 Introduction 11 2.2 Localization Framework 11 2.3 Location-based Services 13 2.3.1 LBS Ecosystem 13 2.3.2 Taxonomies 15 2.3.3 Context Awareness 26 2.3.4 Privacy 29 2.4 Location-based Network Optimization 32 2.4.1 Radio Network Planning 32 2.4.2 Radio Resource Management 32 2.5 Patent Trends 35 2.6 Conclusions 39 3 Basics of Wireless Communications for Positioning 43Gilberto Berardinelli and Nicola Marchetti 3.1 Introduction 43 3.2 Radio Propagation 44 3.2.1 Path Loss 45 3.2.2 Shadowing 48 3.2.3 Small-scale Fading 49 3.2.4 Radio Propagation and Mobile Positioning 52 3.2.5 RSS-based Positioning 54 3.3 Multiple-antenna Techniques 55 3.3.1 Spatial Diversity 55 3.3.2 Spatial Multiplexing 56 3.3.3 Gains Obtained by Exploiting the Spatial Domain 57 3.3.4 MIMO and Mobile Positioning 59 3.4 Duplexing Methods 59 3.4.1 Simplex Systems 59 3.4.2 Half-duplex 59 3.4.3 Full Duplex 60 3.5 Modulation and Multiple-access Techniques 61 3.5.1 Modulation Techniques 61 3.5.2 Multiple-access Techniques 65 3.5.3 OFDMA and Mobile Positioning 67 3.6 Radio Resource Management and Mobile Positioning 67 3.6.1 Handoff, Channel Reuse and Interference Adaptation 67 3.6.2 Power Control 69 3.7 Synchronization 70 3.7.1 Centralized Synchronization 70 3.7.2 Distributed Synchronization 71 3.8 Cooperative Communications 72 3.8.1 Cooperative MIMO 73 3.8.2 Clustering 74 3.8.3 Cooperative Routing 75 3.8.4 RSS-based Cooperative Positioning 75 3.9 Cognitive Radio and Mobile Positioning 75 3.10 Conclusions 78 4 Fundamentals of Positioning 81João Figueiras 4.1 Introduction 81 4.2 Classification of Positioning Infrastructures 81 4.2.1 Positioning-system Topology 82 4.2.2 Physical Coverage Range 83 4.2.3 Integration of Positioning Solutions 84 4.3 Types of Measurements and Methods for their Estimation 85 4.3.1 Cell ID 85 4.3.2 Signal Strength 85 4.3.3 Time of Arrival 86 4.3.4 Time Difference of Arrival 87 4.3.5 Angle of Arrival 88 4.3.6 Personal-information Identification 89 4.4 Positioning Techniques 89 4.4.1 Proximity Sensing 89 4.4.2 Triangulation 91 4.4.3 Fingerprinting 95 4.4.4 Dead Reckoning 98 4.4.5 Hybrid Approaches 98 4.5 Error Sources in Positioning 100 4.5.1 Propagation 100 4.5.2 Geometry 104 4.5.3 Equipment and Technology 105 4.6 Metrics of Location Accuracy 106 4.6.1 Circular Error Probability 106 4.6.2 Dilution of Precision 106 4.6.3 Cramér–Rao Lower Bound 107 4.7 Conclusions 107 5 Data Fusion and Filtering Techniques 109João Figueiras 5.1 Introduction 109 5.2 Least-squares Methods 110 5.2.1 Linear Least Squares 111 5.2.2 Recursive Least Squares 112 5.2.3 Weighted Nonlinear Least Squares 113 5.2.4 The Absolute/Local-minimum Problem 117 5.3 Bayesian Filtering 117 5.3.1 The Kalman Filter 118 5.3.2 The Particle Filter 124 5.3.3 Grid-based Methods 126 5.4 Estimating Model Parameters and Biases in Observations 126 5.4.1 Precalibration 127 5.4.2 Joint Parameter and State Estimation 127 5.5 Alternative Approaches 128 5.5.1 Fingerprinting 128 5.5.2 Time Series Data 131 5.6 Conclusions 132 6 Fundamentals of Tracking 135João Figueiras 6.1 Introduction 135 6.2 Impact of User Mobility on Positioning 136 6.2.1 Localizing Static Devices 136 6.2.2 Added Complexity in Tracking 136 6.2.3 Additional Knowledge in Cooperative Environments 136 6.3 Mobility Models 137 6.3.1 Conventional Models 137 6.3.2 Models Based on Stochastic Processes 137 6.3.3 Geographical-restriction Models 144 6.3.4 Group Mobility Models 146 6.3.5 Social-based Models 147 6.4 Tracking Moving Devices 150 6.4.1 Mitigating Obstructions in the Propagation Conditions 150 6.4.2 Tracking Nonmaneuvering Targets 151 6.4.3 Tracking Maneuvering Targets 152 6.4.4 Learning Position and Trajectory Patterns 155 6.5 Conclusions 160 7 Error Mitigation Techniques 163Ismail Guvenc 7.1 Introduction 163 7.2 System Model 165 7.2.1 Maximum-likelihood Algorithm for LOS Scenarios 166 7.2.2 Cramér–Rao Lower Bounds for LOS Scenarios 167 7.3 NLOS Scenarios: Fundamental Limits and Maximum-likelihood Solutions 170 7.3.1 ML-based Algorithms 170 7.3.2 Cramér–Rao Lower Bound 173 7.4 Least-squares Techniques for NLOS Localization 175 7.4.1 Weighted Least Squares 175 7.4.2 Residual-weighting Algorithm 176 7.5 Constraint-based Techniques for NLOS Localization 178 7.5.1 Constrained LS Algorithm and Quadratic Programming 178 7.5.2 Linear Programming 178 7.5.3 Geometry-constrained Location Estimation 180 7.5.4 Interior-point Optimization 181 7.6 Robust Estimators for NLOS Localization 182 7.6.1 Huber M-estimator 182 7.6.2 Least Median Squares 183 7.6.3 Other Robust Estimation Options 184 7.7 Identify and Discard Techniques for NLOS Localization 184 7.7.1 Residual Test Algorithm 184 7.8 Conclusions 188 8 Positioning Systems and Technologies 189Andreas Waadt, Guido Bruck and Peter Jung 8.1 Introduction 189 8.2 Satellite Positioning 190 8.2.1 Overview 190 8.2.2 Basic Principles 191 8.2.3 Satellite Positioning Systems 194 8.2.4 Accuracy and Reliability 195 8.2.5 Drawbacks When Applied to Mobile Positioning 195 8.3 Cellular Positioning 196 8.3.1 Overview 196 8.3.2 GSM 197 8.3.3 UMTS 206 8.3.4 LTE 208 8.3.5 Emergency Applications in Cellular Networks 211 8.3.6 Drawbacks When Applied to Mobile Positioning 213 8.4 Wireless Local/Personal Area Network Positioning 213 8.4.1 Solutions on Top of Wireless Local Networks 213 8.4.2 Dedicated Solutions 217 8.5 Ad hoc Positioning 220 8.6 Hybrid Positioning 220 8.6.1 Heterogeneous Positioning 220 8.6.2 Cellular and WLAN 221 8.6.3 Assisted GPS 221 8.7 Conclusions 223 Acknowledgements 223 9 Ultra-wideband Positioning and Tracking 225Davide Dardari 9.1 Introduction 225 9.2 UWB Technology 226 9.2.1 History and Definitions 226 9.2.2 Theory 226 9.2.3 Regulations 228 9.3 The UWB Radio Channel 230 9.3.1 Path Loss 231 9.3.2 Multipath 231 9.3.3 UWB Channel Models for Positioning 232 9.4 UWB Standards 233 9.4.1 IEEE 802.15.4a Standard 233 9.4.2 IEEE 802.15.4f Standard 235 9.4.3 Other Standards 237 9.5 Time-of-arrival Measurements 237 9.5.1 Two-way Ranging 237 9.5.2 Time Difference of Arrival 238 9.5.3 Fundamental Limits in TOA Estimation 238 9.5.4 Main Issues in TOA Estimation 240 9.5.5 Clock Drift 242 9.6 Ranging Algoritms in Real Conditions 243 9.6.1 ML TOA Estimation in the Presence of a Multipath 243 9.6.2 Clock Drift Mitigation 248 9.6.3 Localization and Tracking with UWB 250 9.7 Passive UWB Localization 253 9.7.1 UWB-RFID 253 9.8 Conclusions and Perspectives 258 Acknowledgments 260 10 Indoor Positioning in WLAN 261Francescantonio Della Rosa, Mauro Pelosi and Jari Nurmi 10.1 Introduction 261 10.2 Potential and Limitations of WLAN 262 10.3 Empirical Approaches 263 10.3.1 Probe Requests and Beacon Frames 264 10.3.2 Positioning Methods 265 10.3.3 Evaluation Criteria for Indoor Positioning Systems Based on WLANs 272 10.4 Error Sources in RSS Measurements 274 10.4.1 Heterogeneous WiFi Cards 275 10.4.2 Device Orientation 277 10.4.3 Channel in the Presence of the User and Body Loss 278 10.4.4 The Hand Grip 278 10.5 Experimental Activities 279 10.6 Conclusions 281 11 Cooperative Multi-tag Localization in RFID Systems: Exploiting Multiplicity, Diversity and Polarization of Tags 283Tanveer Bhuiyan and Simone Frattasi 11.1 Introduction 283 11.2 RFID Positioning Systems 285 11.2.1 Single-tag Localization 285 11.3 Cooperative Multi-tag Localization 286 11.3.1 Multi-tagged Objects and Persons 286 11.3.2 Localization of Mobile RFID Readers: CoopAOA 290 11.3.3 Performance Evaluation 297 11.3.4 Experimental Activity for Tag Localization 309 11.4 Conclusions 314 12 Cooperative Mobile Positioning 315Simone Frattasi, Joaõ Figueiras and Francescantonio Della Rosa 12.1 Introduction 315 12.2 Cooperative Localization 316 12.2.1 Robot Networks 316 12.2.2 Wireless Sensor Networks 317 12.2.3 Wireless Mobile Networks 321 12.3 Cooperative Data Fusion and Filtering Techniques 323 12.3.1 Coop-WNLLS: Cooperative Weighted Nonlinear Least Squares 323 12.3.2 Coop-EKF: Cooperative Extended Kalman Filter 326 12.4 COMET: A Cooperative Mobile Positioning System 328 12.4.1 System Architecture 328 12.4.2 Data Fusion Methods 330 12.4.3 Performance Evaluation 337 12.5 Experimental Activity in a Cooperative WLAN Scenario 349 12.5.1 Scenario 350 12.5.2 Results 350 12.6 Conclusions 352 References 353 Index 373

Read more less

Book SynopsisA comprehensive and invaluable guide to 5G technology, implementation and practice in one single volume. For all things 5G, this book is a must-read. Signal processing techniques have played the most important role in wireless communications since the second generation of cellular systems. It is anticipated that new techniques employed in 5G wireless networks will not only improve peak service rates significantly, but also enhance capacity, coverage, reliability , low-latency, efficiency, flexibility, compatibility and convergence to meet the increasing demands imposed by applications such as big data, cloud service, machine-to-machine (M2M) and mission-critical communications. This book is a comprehensive and detailed guide to all signal processing techniques employed in 5G wireless networks. Uniquely organized into four categories, New Modulation and Coding, New Spatial Processing, New Spectrum Opportunities and New System-level Enabling TechnoloTable of ContentsPreface xvii List of Contributors xxv Part I MODULATION, CODING AND WAVEFORM FOR 5G 1 An Introduction to Modulations and Waveforms for 5G Networks 3Stefano Buzzi, Alessandro Ugolini, Alessio Zappone and Giulio Colavolpe 1.1 Motivation and Background 3 1.2 New Modulation Formats: FBMC, GFDM, BFDM, UFMC and TFP 7 1.3 Waveform Choice 19 1.4 Discussion and Concluding Remarks 20 References 22 2 Faster-than-Nyquist Signaling for 5G Communication 24John B. Anderson 2.1 Introduction to FTN Signaling 25 2.2 Time FTN: Receivers and Performance 32 2.3 Frequency FTN Signaling 41 2.4 Summary of the Chapter 45 References 46 3 From OFDM to FBMC: Principles and Comparisons 47Wei Jiang and Thomas Kaiser 3.1 Introduction 47 3.2 The Filter Bank 49 3.3 Polyphase Implementation 53 3.4 OFDM 55 3.5 FBMC 61 3.6 Comparison of FBMC and Filtered OFDM 62 3.7 Conclusion 65 References 66 4 Filter Bank Multicarrier for Massive MIMO 67Arman Farhang, Nicola Marchetti and Behrouz Farhang-Boroujeny 4.1 System Model and FBMC Formulation in Massive MIMO 69 4.2 Self-equalization Property of FBMC in Massive MIMO 74 4.3 Comparison with OFDM 80 4.4 Blind Equalization and Pilot Decontamination 82 4.5 Conclusion 87 References 88 5 Bandwidth-compressed Multicarrier Communication: SEFDM 90Izzat Darwazeh, Tongyang Xu and Ryan C Grammenos 5.1 Introduction 91 5.2 SEFDM Fundamentals 93 5.3 Block-SEFDM 97 5.4 Turbo-SEFDM 102 5.5 Practical Considerations and Experimental Demonstration 106 5.6 Summary 112 References 112 6 Non-orthogonal Multi-User Superposition and Shared Access 115Yifei Yuan 6.1 Introduction 115 6.2 Basic Principles and Features of Non-orthogonal Multi-user Access 116 6.3 Downlink Non-orthogonal Multi-user Transmission 121 6.4 Uplink Non-orthogonal Multi-user Access 129 6.5 Summary and Future Work 140 References 142 7 Non-Orthogonal Multiple Access (NOMA): Concept and Design 143Anass Benjebbour, Keisuke Saito, Anxin Li, Yoshihisa Kishiyama and Takehiro Nakamura 7.1 Introduction 143 7.2 Concept 145 7.3 Benefits and Motivations 148 7.4 Interface Design 150 7.5 MIMO Support 153 7.6 Performance Evaluations 157 7.7 Conclusion 166 References 167 8 Major 5G Waveform Candidates: Overview and Comparison 169Hao Lin and Pierre Siohan 8.1 Why We Need New Waveforms 170 8.2 Major Multicarrier Modulation Candidates 171 8.3 High-level Comparison 178 8.4 Conclusion 184 List of acronyms 185 References 186 Part II NEW SPATIAL SIGNAL PROCESSING FOR 5G 9 Massive MIMO for 5G: Theory, Implementation and Prototyping 191Ove Edfors, Liang Liu, Fredrik Tufvesson, Nikhil Kundargi and Karl Nieman 9.1 Introduction 192 9.2 Massive MIMO Theory 194 9.3 Massive MIMO Channels 199 9.4 Massive MIMO Implementation 204 9.5 Testbed Design 214 9.6 Synchronization 224 9.7 Future Challenges and Conclusion 227 Acknowledgments 228 References 228 10 Millimeter-Wave MIMO Transceivers: Theory, Design and Implementation 231Akbar M. Sayeed and John H. Brady 10.1 Introduction 232 10.2 Overview of Millimeter-Wave MIMO Transceiver Architectures 235 10.3 Point-to-Point Single-User Systems 237 10.4 Point-to-Multipoint Multiuser Systems 243 10.5 Extensions 249 10.6 Conclusion 250 References 251 11 3D Propagation Channels: Modeling and Measurements 254Andreas F. Molisch 11.1 Introduction and Motivation 255 11.2 Measurement Techniques 257 11.3 Propagation Effects 260 11.4 Measurement Results 263 11.5 Channel Models 266 11.6 Summary and Open Issues 268 Acknowledgements 269 Disclaimer 269 References 269 12 3D-MIMO with Massive Antennas: Theory, Implementation and Testing 273Guangyi Liu, Xueying Hou, Fei Wang, Jing Jin and Hui Tong 12.1 Introduction 274 12.2 Application Scenarios of 3D-MIMO with Massive Antennas 276 12.3 Exploiting 3D-MIMO Gain Based on Techniques in Current Standards 277 12.4 Evaluation by System-level Simulations 283 12.5 Field Trials of 3D-MIMO with Massive Antennas 288 12.6 Achieving 3D-MIMO with Massive Antennas from Theory to Practice 292 12.7 Conclusions 294 References 295 13 Orbital Angular Momentum-based Wireless Communications: Designs and Implementations 296Alan. E. Willner, Yan Yan, Yongxiong Ren, Nisar Ahmed and Guodong Xie 13.1 EM Waves Carrying OAM 297 13.2 Application of OAM to RF Communications 298 13.3 OAM Beam Generation, Multiplexing and Detection 300 13.4 Wireless Communications Using OAM Multiplexing 303 13.5 Summary and Perspective 315 References 316 Part III NEW SPECTRUM OPPORTUNITIES FOR 5G 14 MillimeterWaves for 5G: From Theory To Practice 321Malik Gul, Eckhard Ohlmer, Ahsan Aziz, Wes McCoy and Yong Rao 14.1 Introduction 321 14.2 Building a mmWave PoC System 322 14.3 Desirable Features of a mmWave Prototyping System 323 14.4 Case Study: a mmWave Cellular PoC 326 14.5 Conclusion 352 References 353 15 *5G Millimeter-wave Communication Channel and Technology Overview 354Qian (Clara) Li, Hyejung Jung, Pingping Zong and Geng Wu 15.1 Introduction 354 15.2 Millimeter-wave Channel Characteristics 355 15.3 Requirements for a 5G mmWave Channel Model 357 15.4 Millimeter-wave Channel Model for 5G 358 15.5 Signal Processing for mmWave Band 5G RAT 365 15.6 Summary 370 References 371 16 General Principles and Basic Algorithms for Full-duplex Transmission 372Thomas Kaiser and Nidal Zarifeh 16.1 Introduction 373 16.2 Self-interference: Basic Analyses and Models 374 16.3 SIC Techniques and Algorithms 376 16.4 Hardware Impairments and Implementation Challenges 386 16.5 Looking Toward Full-duplex MIMO Systems 393 16.6 Conclusion and Outlook 396 References 397 17 Design and Implementation of Full-duplex Transceivers 402Katsuyuki Haneda, Mikko Valkama, Taneli Riihonen, Emilio Antonio-Rodriguez and Dani Korpi 17.1 Research Challenges 405 17.2 Antenna Designs 409 17.3 RF Self-interference Cancellation Methods 411 17.4 Digital Self-interference Cancellation Algorithms 413 17.5 Demonstration 423 17.6 Summary 426 Acknowledgements 426 References 426 Part IV NEW SYSTEM-LEVEL ENABLING TECHNOLOGIES FOR 5G 18 Cloud Radio Access Networks: Uplink Channel Estimation and Downlink Precoding 431Osvaldo Simeone, Jinkyu Kang, Joonkhyuk Kang and Shlomo Shamai (Shitz) 18.1 Introduction 432 18.2 Technology Background 432 18.3 Uplink: Where to Perform Channel Estimation? 434 18.4 Downlink: Where to Perform Channel Encoding and Precoding? 441 18.5 Concluding Remarks 453 References 454 19 Energy-efficient Resource Allocation in 5G with Application to D2D 456Alessio Zappone, Francesco Di Stasio, Stefano Buzzi and Eduard Jorswieck 19.1 Introduction 457 19.2 Signal Model 459 19.3 Resource Allocation 461 19.4 Fractional Programming 462 19.5 Algorithms 466 19.6 Sequential Fractional Programming 469 19.7 System Optimization 471 19.8 Numerical Results 476 19.9 Conclusion 480 References 481 20 Ultra Dense Networks: General Introduction and Design Overview 483Jianchi Zhu, Xiaoming She and Peng Chen 20.1 Introduction 484 20.2 Interference Management 487 20.3 Mobility Management 495 20.4 Architecture and Backhaul 499 20.5 Other Issues in UDNs for 5G 503 20.6 Conclusions 505 Acknowledgements 506 References 506 21 Radio-resource Management and Optimization in 5G Networks 509Antonis Gotsis, Athanasios Panagopoulos, Stelios Stefanatos and Angeliki Alexiou 21.1 Introduction 510 21.2 Background 511 21.3 Optimal Strategies for Single-antenna Coordinated Ultradense Networks 514 21.4 Optimal Strategies for Multi-antenna Coordinated and Cooperative Ultradense Networks 525 21.5 Summary and Future Research Directions 533 Acknowledgments 534 References 534 Part V REFERENCE DESIGN AND 5G STANDARD DEVELOPMENT 22 Full-duplex Radios in 5G: Fundamentals, Design and Prototyping 539Jaeweon Kim, Min Soo Sim, MinKeun Chung, Dong Ku Kim and Chan-Byoung Chae 22.1 Introduction 540 22.2 Self-interference 541 22.3 Analog Self-interference Cancellation 542 22.4 Digital Self-interference Cancellation 547 22.5 Prototyping Full-duplex Radios 550 22.6 Overall Performance Evaluation 558 22.7 Conclusion 559 References 559 23 5G Standard Development: Technology and Roadmap 561Juho Lee and Yongjun Kwak 23.1 Introduction 561 23.2 Standards Roadmap from 4G to 5G 562 23.3 Preparation of 5G Cellular Communication Standards 570 23.4 Concluding Remarks 575 References 575 Index 577

Read more less

Book SynopsisThe book examines how Fog will change the information technology industry in the next decade. Fog distributes the services of computation, communication, control and storage closer to the edge, access and users. As a computing and networking architecture, Fog enables key applications in wireless 5G, the Internet of Things, and big data.Table of ContentsContributors xi Introduction 1Bharath Balasubramanian, Mung Chiang, and Flavio Bonomi I.1 Summary of Chapters 5 I.2 Acknowledgments 7 References 8 I Communication and Management of Fog 11 1 ParaDrop: An Edge Computing Platform in Home Gateways 13Suman Banerjee, Peng Liu, Ashish Patro, and Dale Willis 1.1 Introduction 13 1.1.1 Enabling Multitenant Wireless Gateways and Applications through ParaDrop 14 1.1.2 ParaDrop Capabilities 15 1.2 Implementing Services for the ParaDrop Platform 17 1.3 Develop Services for ParaDrop 19 1.3.1 A Security Camera Service Using ParaDrop 19 1.3.2 An Environmental Sensor Service Using ParaDrop 22 References 23 2 Mind Your Own Bandwidth 24Carlee Joe-Wong, Sangtae Ha, Zhenming Liu, Felix Ming Fai Wong, and Mung Chiang 2.1 Introduction 24 2.1.1 Leveraging the Fog 25 2.1.2 A Home Solution to a Home Problem 25 2.2 Related Work 28 2.3 Credit Distribution and Optimal Spending 28 2.3.1 Credit Distribution 29 2.3.2 Optimal Credit Spending 31 2.4 An Online Bandwidth Allocation Algorithm 32 2.4.1 Estimating Other Gateways’ Spending 32 2.4.2 Online Spending Decisions and App Prioritization 34 2.5 Design and Implementation 35 2.5.1 Traffic and Device Classification 37 2.5.2 Rate Limiting Engine 37 2.5.3 Traffic Prioritization Engine 38 2.6 Experimental Results 39 2.6.1 Rate Limiting 39 2.6.2 Traffic Prioritization 41 2.7 Gateway Sharing Results 41 2.8 Concluding Remarks 45 Acknowledgments 46 Appendix 2.A 46 2.A.1 Proof of Lemma 2.1 46 2.A.2 Proof of Lemma 2.2 46 2.A.3 Proof of Proposition 2.1 47 2.A.4 Proof of Proposition 2.2 48 2.A.5 Proof of Proposition 2.3 49 2.A.6 Proof of Proposition 2.4 49 References 50 3 Socially-Aware Cooperative D2D and D4D Communications toward Fog Networking 52Xu Chen, Junshan Zhang, and Satyajayant Misra 3.1 Introduction 52 3.1.1 From Social Trust and Social Reciprocity to D2D Cooperation 54 3.1.2 Smart Grid: An IoT Case for Socially-Aware Cooperative D2D and D4D Communications 55 3.1.3 Summary of Main Results 57 3.2 Related Work 58 3.3 System Model 59 3.3.1 Physical (Communication) Graph Model 60 3.3.2 Social Graph Model 61 3.4 Socially-Aware Cooperative D2D and D4D Communications toward Fog Networking 62 3.4.1 Social Trust-Based Relay Selection 63 3.4.2 Social Reciprocity-Based Relay Selection 63 3.4.3 Social Trust and Social Reciprocity-Based Relay Selection 68 3.5 Network Assisted Relay Selection Mechanism 69 3.5.1 Reciprocal Relay Selection Cycle Finding 69 3.5.2 NARS Mechanism 70 3.5.3 Properties of NARS Mechanism 73 3.6 Simulations 75 3.6.1 Erdos–Renyi Social Graph 76 3.6.2 Real Trace Based Social Graph 78 3.7 Conclusion 82 Acknowledgments 82 References 83 4 You Deserve Better Properties (From Your Smart Devices) 86Steven Y. Ko 4.1 Why We Need to Provide Better Properties 86 4.2 Where We Need to Provide Better Properties 87 4.3 What Properties We Need to Provide and How 88 4.3.1 Transparency 88 4.3.2 Predictable Performance 93 4.3.3 Openness 99 4.4 Conclusions 102 Acknowledgment 102 References 103 II Storage and Computation in Fog 107 5 Distributed Caching for Enhancing Communications Efficiency 109A. Salman Avestimehr and Andreas F. Molisch 5.1 Introduction 109 5.2 Femtocaching 111 5.2.1 System Model 111 5.2.2 Adaptive Streaming from Helper Stations 114 5.3 User-Caching 115 5.3.1 Cluster-Based Caching and D2D Communications 115 5.3.2 IT LinQ-Based Caching and Communications 118 5.3.3 Coded Multicast 126 5.4 Conclusions and Outlook 130 References 131 6 Wireless Video Fog: Collaborative Live Streaming with Error Recovery 133Bo Zhang, Zhi Liu, and S.-H. Gary Chan 6.1 Introduction 133 6.2 Related Work 136 6.3 System Operation and Network Model 138 6.4 Problem Formulation and Complexity 140 6.4.1 NC Packet Selection Optimization 140 6.4.2 Broadcaster Selection Optimization 143 6.4.3 Complexity Analysis 144 6.5 VBCR: A Distributed Heuristic for Live Video with Cooperative Recovery 144 6.5.1 Initial Information Exchange 145 6.5.2 Cooperative Recovery 145 6.5.3 Updated Information Exchange 147 6.5.4 Video Packet Forwarding 147 6.6 Illustrative Simulation Results 150 6.7 Concluding Remarks 156 References 156 7 Elastic Mobile Device Clouds: Leveraging Mobile Devices to Provide Cloud Computing Services at the Edge 159Karim Habak, Cong Shi, Ellen W. Zegura, Khaled A. Harras, and Mostafa Ammar 7.1 Introduction 159 7.2 Design Space with Examples 161 7.2.1 Mont-Blanc 162 7.2.2 Computing while Charging 163 7.2.3 FemtoCloud 164 7.2.4 Serendipity 166 7.3 FemtoCloud Performance Evaluation 168 7.3.1 Experimental Setup 168 7.3.2 FemtoCloud Simulation Results 169 7.3.3 FemtoCloud Prototype Evaluation 173 7.4 Serendipity Performance Evaluation 175 7.4.1 Experimental Setup 175 7.4.2 Serendipity’s Performance Benefits 176 7.4.3 Impact of Network Environment 179 7.4.4 The Impact of the Job Properties 182 7.5 Challenges 186 References 186 III Applications of Fog 189 8 The Role of Fog Computing in the Future of the Automobile 191Flavio Bonomi, Stefan Poledna, and Wilfried Steiner 8.1 Introduction 191 8.2 Current Automobile Electronic Architectures 193 8.3 Future Challenges of Automotive E/E Architectures and Solution Strategies 195 8.4 Future Automobiles as Fog Nodes on Wheels 200 8.5 Deterministic FOG Nodes on Wheels Through Real-Time Computing and Time-Triggered Technologies 203 8.5.1 Deterministic Fog Node Addressing the Scalability Challenge through Virtualization 203 8.5.2 Deterministic Fog Node Addressing the Connectivity and Security Challenges 204 8.5.3 Emerging Use Case of Deterministic Fog Nodes in Automotive Applications—Vehicle-Wide Virtualization 206 8.6 Conclusion 209 References 209 9 Geographic Addressing for Field Networks 211Robert J. Hall 9.1 Introduction 211 9.1.1 Field Networking 211 9.1.2 Challenges of Field Networking 212 9.2 Geographic Addressing 214 9.3 SAGP: Wireless GA in the Field 215 9.3.1 SAGP Processing 216 9.3.2 SAGP Retransmission Heuristics 217 9.3.3 Example of SAGP Packet Propagation 218 9.3.4 Followcast: Efficient SAGP Streaming 219 9.3.5 Meeting the Challenges 220 9.4 Georouting: Extending GA to the Cloud 221 9.5 SGAF: A Multi-Tiered Architecture for Large-Scale GA 222 9.5.1 Bridging Between Tiers 223 9.5.2 Hybrid Security Architecture 225 9.6 The AT&T Labs Geocast System 225 9.7 Two GA Applications 226 9.7.1 PSCommander 226 9.7.2 Geocast Games 230 9.8 Conclusions 232 References 232 10 Distributed Online Learning and Stream Processing for a Smarter Planet 234Deepak S. Turaga and Mihaela van der Schaar 10.1 Introduction: Smarter Planet 234 10.2 Illustrative Problem: Transportation 237 10.3 Stream Processing Characteristics 238 10.4 Distributed Stream Processing Systems 239 10.4.1 State of the Art 239 10.4.2 Stream Processing Systems 240 10.5 Distributed Online Learning Frameworks 244 10.5.1 State of the Art 244 10.5.2 Systematic Framework for Online Distributed Ensemble Learning 247 10.5.3 Online Learning of the Aggregation Weights 250 10.5.4 Collision Detection Application 254 10.6 What Lies Ahead 257 Acknowledgment 258 References 258 11 Securing the Internet of Things: Need for a New Paradigm and Fog Computing 261Tao Zhang, Yi Zheng, Raymond Zheng, and Helder Antunes 11.1 Introduction 261 11.2 New IoT Security Challenges That Necessitate Fundamental Changes to the Existing Security Paradigm 263 11.2.1 Many Things Will Have Long Life Spans but Constrained and Difficult-to-Upgrade Resources 264 11.2.2 Putting All IoT Devices Inside Firewalled Castles Will Become Infeasible or Impractical 264 11.2.3 Mission-Critical Systems Will Demand Minimal-Impact Incident Responses 265 11.2.4 The Need to Know the Security Status of a Vast Number of Devices 266 11.3 A New Security Paradigm for the Internet of Things 268 11.3.1 Help the Less Capable with Fog Computing 269 11.3.2 Scale Security Monitoring to Large Number of Devices with Crowd Attestation 272 11.3.3 Dynamic Risk–Benefit-Proportional Protection with Adaptive Immune Security 277 11.4 Summary 281 Acknowledgment 281 References 281 Index 285

Read more less

Book SynopsisThis book addresses researchers and graduate students at the forefront of study/research on the Internet of Things (IoT) by presenting state-of-the-art research together with the current and future challenges in building new smart applications (e.g., Smart Cities, Smart Buildings, and Industrial IoT) in an efficient, scalable, and sustainable way. It covers the main pillars of the IoT world (Connectivity, Interoperability, Discoverability, and Security/Privacy), providing a comprehensive look at the current technologies, procedures, and architectures.Table of ContentsPreface xv 1 Preliminaries, Motivation, and Related Work 1 1.1 What is the Internet of Things? 1 1.2 Wireless Ad-hoc and Sensor Networks:The Ancestors without IP 2 1.3 IoT-enabled Applications 3 1.3.1 Home and Building Automation 3 1.3.2 Smart Cities 4 1.3.3 Smart Grids 4 1.3.4 Industrial IoT 5 1.3.5 Smart Farming 7 2 Standards 9 2.1 “Traditional” Internet Review 9 2.1.1 Physical/Link Layer 10 2.1.1.1 IEEE 802.3 (Ethernet) 11 2.1.1.2 IEEE 802.11 12 2.1.2 Network Layer 14 2.1.2.1 IPv6 and IPv4 14 2.1.3 Transport Layer 17 2.1.3.1 TCP and UDP 19 2.1.4 Application Layer 21 2.1.4.1 HTTP 21 2.1.4.2 AMQP 22 2.1.4.3 SIP 23 2.2 The Internet ofThings 25 2.2.1 Designing the Architecture of an IP-based Internet of Things 26 2.2.2 Physical/Link Layer 28 2.2.2.1 IEEE 802.15.4 and ZigBee 28 2.2.2.2 Low-powerWi-Fi 30 2.2.2.3 Bluetooth and BLE 31 2.2.2.4 Powerline Communications 32 2.2.3 Network Layer 33 2.2.3.1 The 6LoWPAN Adaptation Layer 34 2.2.4 Transport Layer 34 2.2.5 Application Layer 34 2.2.5.1 CoAP 35 2.2.5.2 CoSIP Protocol Specification 60 2.3 The Industrial IoT 76 3 Interoperability 79 3.1 Applications in the IoT 79 3.2 The Verticals: Cloud-based Solutions 80 3.3 REST Architectures:TheWeb of Things 81 3.3.1 REST: TheWeb as a Platform 82 3.3.1.1 Resource-oriented Architectures 83 3.3.1.2 REST Architectures 84 3.3.1.3 Representation of Resources 84 3.3.1.4 Resource Identifiers 85 3.3.1.5 Statelessness 86 3.3.1.6 Applications as Finite-state Machines 86 3.3.1.7 Hypermedia as the Engine of Application State 86 3.3.2 Richardson MaturityModel 88 3.3.2.1 Level 0: the Swamp of POX 88 3.3.2.2 Level 1: Resources 90 3.3.2.3 Level 2: HTTP Verbs 90 3.3.2.4 Level 3: Hypermedia 95 3.3.2.5 The Meaning of the Levels 97 3.4 TheWeb of Things 97 3.5 Messaging Queues and Publish/Subscribe Communications 98 3.5.1 Advantages of the Pub/Sub Model 99 3.5.2 Disadvantages of the Pub/Sub Model 100 3.5.3 Message Queue Telemetry Transport 100 3.5.3.1 MQTT versus AMQP 101 3.6 Session Initiation for the IoT 102 3.6.1 Motivations 102 3.6.2 Lightweight Sessions in the IoT 104 3.6.2.1 A Protocol for Constrained Session Initiation 106 3.6.2.2 Session Initiation 106 3.6.2.3 Session Tear-down 108 3.6.2.4 Session Modification 108 3.7 Performance Evaluation 109 3.7.1 Implementation 109 3.7.2 Experimental Results 111 3.7.3 Conclusions 114 3.8 Optimized Communications: the Dual-network Management Protocol 115 3.8.1 DNMP Motivations 115 3.8.2 RelatedWork 117 3.8.3 The DNMP Protocol 118 3.8.4 Implementation with IEEE 802.15.4 and IEEE 802.11s 123 3.8.4.1 LPLT Networking 123 3.8.4.2 HPHT Networking 123 3.8.4.3 Node Integration 124 3.8.5 Performance Evaluation 125 3.8.5.1 Experimental Setup 125 3.8.5.2 Operational Limitations of IEEE 802.15.4 126 3.8.6 IEEE 802.15.4-controlled Selective Activation of the IEEE 802.11s Network 129 3.8.7 Conclusions 130 3.9 Discoverability in Constrained Environments 131 3.9.1 CoRE Link Format 131 3.9.1.1 CoRE Link Format: Discovery 132 3.9.1.2 Link Format 133 3.9.1.3 The Interface Description Attribute 135 3.9.2 CoRE Interfaces 135 3.9.2.1 Sensor 136 3.9.2.2 Parameter 137 3.9.2.3 Read-only Parameter 137 3.9.2.4 Actuator 137 3.10 Data Formats: Media Types for Sensor Markup Language 138 3.10.1 JSON Representations 141 3.10.1.1 Single Datapoint 141 3.10.1.2 Multiple Datapoints 142 3.10.1.3 Multiple Measurements 142 4 Discoverability 145 4.1 Service and Resource Discovery 145 4.2 Local and Large-scale Service Discovery 146 4.2.1 ZeroConf 151 4.2.2 UPnP 152 4.2.3 URI Beacons and the PhysicalWeb 152 4.3 Scalable and Self-configuring Architecture for Service Discovery in the IoT 154 4.3.1 IoT Gateway 156 4.3.1.1 Proxy Functionality 156 4.3.1.2 Service and Resource Discovery 158 4.3.2 A P2P-based Large-scale Service Discovery Architecture 159 4.3.2.1 Distributed Location Service 160 4.3.2.2 Distributed Geographic Table 161 4.3.2.3 An Architecture for Large-scale Service Discovery based on Peer-to-peer Technologies 162 4.3.3 Zeroconf-based Local Service Discovery for Constrained Environments 167 4.3.3.1 Architecture 167 4.3.3.2 Service Discovery Protocol 168 4.3.4 Implementation Results 170 4.3.4.1 Local Service Discovery 171 4.3.4.2 Large-scale Service Discovery 175 4.4 Lightweight Service Discovery in Low-power IoT Networks 178 4.4.1 Efficient Forwarding Protocol for Service Discovery 180 4.4.1.1 Multicast through Local Filtered Flooding 181 4.4.2 Efficient Multiple Unicast Forwarding 183 4.5 Implementation Results 185 5 Security and Privacy in the IoT 191 5.1 Security Issues in the IoT 192 5.2 Security Mechanisms Overview 196 5.2.1 Traditional vs Lightweight security 196 5.2.1.1 Network Layer 197 5.2.1.2 Transport Layer 199 5.2.1.3 Application Layer 201 5.2.2 Lightweight Cryptography 202 5.2.2.1 Symmetric-key LWC Algorithms 203 5.2.2.2 Public-key (Asymmetric) LWC Algorithms 206 5.2.2.3 Lightweight Cryptographic Hash Functions 210 5.2.2.4 Homomorphic Encryption Schemes 213 5.2.3 Key Agreement, Distribution, and Security Bootstrapping 214 5.2.3.1 Key Agreement Protocols 215 5.2.3.2 Shared Group-key Distribution 215 5.2.3.3 Security Bootstrapping 216 5.2.4 Processing Data in the Encrypted Domain: Secure Data Aggregation 217 5.2.5 Authorization Mechanisms for Secure IoT Services 219 5.3 Privacy Issues in the IoT 222 5.3.1 The Role of Authorization 222 5.3.2 IoT-OAS: Delegation-based Authorization for the Internet of Things 227 5.3.2.1 Architecture 227 5.3.2.2 Granting Access Tokens 229 5.3.2.3 Authorizing Requests 231 5.3.2.4 SP-to-IoT-OAS Communication: Protocol Details 231 5.3.2.5 Configuration 232 5.3.3 IoT-OAS Application Scenarios 232 5.3.3.1 Network Broker Communication 233 5.3.3.2 Gateway-based Communication 235 5.3.3.3 End-to-End CoAP Communication 235 5.3.3.4 Hybrid Gateway-based Communication 235 6 Cloud and Fog Computing for the IoT 237 6.1 Cloud Computing 237 6.2 Big Data Processing Pattern 238 6.3 Big Stream 239 6.3.1 Big-stream-oriented Architecture 243 6.3.2 Graph-based Processing 247 6.3.3 Implementation 251 6.3.3.1 Acquisition Module 251 6.3.3.2 Normalization Module 253 6.3.3.3 Graph Framework 254 6.3.3.4 Application Register Module 255 6.3.4 Performance Evaluation 257 6.3.5 Solutions and Security Considerations 262 6.4 Big Stream and Security 263 6.4.1 Graph-based Cloud System Security 266 6.4.2 Normalization after a Secure Stream Acquisition with OFS Module 268 6.4.3 Enhancing the Application Register with the IGS Module 269 6.4.4 Securing Streams inside Graph Nodes 273 6.4.5 Evaluation of a Secure Big Stream Architecture 277 6.5 Fog Computing and the IoT 281 6.6 The Role of the IoTHub 283 6.6.1 Virtualization and Replication 285 6.6.1.1 The IoT Hub 285 6.6.1.2 Operational Scenarios 287 6.6.1.3 Synchronization Protocol 290 7 The IoT in Practice 303 7.1 Hardware for the IoT 303 7.1.1 Classes of Constrained Devices 305 7.1.2 Hardware Platforms 307 7.1.2.1 TelosB 307 7.1.2.2 Zolertia Z1 307 7.1.2.3 OpenMote 310 7.1.2.4 Arduino 313 7.1.2.5 Intel Galileo 315 7.1.2.6 Raspberry Pi 318 7.2 Software for the IoT 321 7.2.1 OpenWSN 321 7.2.2 TinyOS 322 7.2.3 FreeRTOS 323 7.2.4 TI-RTOS 323 7.2.5 RIOT 324 7.2.6 Contiki OS 325 7.2.6.1 Networking 325 7.2.6.2 Low-power Operation 326 7.2.6.3 Simulation 326 7.2.6.4 Programming Model 327 7.2.6.5 Features 328 7.3 Vision and Architecture of a Testbed for theWeb of Things 328 7.3.1 An All-IP-based Infrastructure for Smart Objects 330 7.3.2 Enabling Interactions with Smart Objects through the IoT Hub 332 7.3.2.1 Integration Challenges 334 7.3.3 Testbed Access and Security 335 7.3.3.1 The Role of Authorization 335 7.3.4 Exploiting the Testbed:WoT Applications for Mobile and Wearable Devices 336 7.3.5 Open Challenges and Future Vision 338 7.4 Wearable Computing for the IoT: Interaction Patterns with Smart Objects in RESTful Environments 340 7.4.1 Shaping the Internet ofThings in a Mobile-Centric World 340 7.4.2 Interaction Patterns with Smart Objects throughWearable Devices 342 7.4.2.1 Smart Object Communication Principles 342 7.4.2.2 Interaction Patterns 343 7.4.3 Implementation in a Real-world IoT Testbed 345 7.4.3.1 Future Vision: towards the Tactile Internet 348 7.5 Effective Authorization for theWeb ofThings 349 7.5.1 Authorization Framework Architecture 353 7.5.1.1 System Operations 353 7.5.2 Implementation and Validation 357 Reference 359 Index 381

Read more less

Book SynopsisExplores the fundamentals required to understand, analyze, and implement space modulation techniques (SMTs) in coherent and non-coherent radio frequency environments This book focuses on the concept of space modulation techniques (SMTs), and covers those emerging high data rate wireless communication techniques. The book discusses the advantages and disadvantages of SMTs along with their performance. A general framework for analyzing the performance of SMTs is provided and used to detail their performance over several generalized fading channels. The book also addresses the transmitter design of these techniques with the optimum number of hardware components and the use of these techniques in cooperative and mm-Wave communications. Beginning with an introduction to the subject and a brief history, Space Modulation Techniques goes on to offer chapters covering MIMO systems like spatial multiplexing and space-time coding. It then looks at channel models, such as Rayleigh, Rician, NakaTable of ContentsPreface xiii 1 Introduction 1 1.1 Wireless History 1 1.2 MIMO Promise 2 1.3 Introducing Space Modulation Techniques (SMTs) 3 1.4 Advanced SMTs 4 1.4.1 Space–Time Shift Keying (STSK) 4 1.4.2 Index Modulation (IM) 4 1.4.3 Differential SMTs 5 1.4.4 OpticalWireless SMTs 6 1.5 Book Organization 6 2 MIMO System and ChannelModels 9 2.1 MIMO System Model 9 2.2 SpatialMultiplexing MIMO Systems 11 2.3 MIMO Capacity 11 2.4 MIMO ChannelModels 13 2.4.1 Rayleigh Fading 15 2.4.2 Nakagami-n (Rician Fading) 15 2.4.3 Nakagami-m Fading 16 2.4.4 The ;;–;; MIMO Channel 17 2.4.5 The ;;–;; Distribution 20 2.4.6 The ;;–;; Distribution 23 2.5 Channel Imperfections 26 2.5.1 Spatial Correlation 26 2.5.1.1 Simulating SC Matrix 29 2.5.1.2 Effect of SC on MIMO Capacity 31 2.5.2 Mutual Coupling 31 2.5.2.1 Effect of MC on MIMO Capacity 33 2.5.3 Channel Estimation Errors 34 2.5.3.1 Impact of Channel Estimation Error on the MIMO Capacity 34 3 SpaceModulation Transmission and Reception Techniques 35 3.1 Space Shift Keying (SSK) 36 3.2 Generalized Space Shift Keying (GSSK) 39 3.3 SpatialModulation (SM) 41 3.4 Generalized SpatialModulation (GSM) 44 3.5 Quadrature Space Shift Keying (QSSK) 45 3.6 Quadrature SpatialModulation (QSM) 48 3.7 Generalized QSSK (GQSSK) 53 3.8 Generalized QSM (GQSM) 55 3.9 Advanced SMTs 55 3.9.1 Differential Space Shift Keying (DSSK) 55 3.9.2 Differential SpatialModulation (DSM) 60 3.9.3 Differential Quadrature SpatialModulation (DQSM) 60 3.9.4 Space–Time Shift Keying (STSK) 65 3.9.5 Trellis Coded-Spatial Modulation (TCSM) 66 3.10 Complexity Analysis of SMTs 69 3.10.1 Computational Complexity of the ML Decoder 69 3.10.2 Low-Complexity Sphere Decoder Receiver for SMTs 70 3.10.2.1 SMT-Rx Detector 70 3.10.2.2 SMT-Tx Detector 71 3.10.2.3 Single Spatial Symbol SMTs (SS-SMTs) 71 3.10.2.4 Double Spatial Symbols SMTs (DS-SMTs) 72 3.10.2.5 Computational Complexity 73 3.10.2.6 Error Probability Analysis and Initial Radius 74 3.11 Transmitter Power Consumption Analysis 75 3.11.1 Power Consumption Comparison 77 3.12 Hardware Cost 80 3.12.1 Hardware Cost Comparison 81 3.13 SMTs Coherent and Noncoherent Spectral Efficiencies 82 4 Average Bit Error Probability Analysis for SMTs 85 4.1 Average Error Probability over Rayleigh Fading Channels 85 4.1.1 SM and SSK with Perfect Channel Knowledge at the Receiver 85 4.1.1.1 Single Receive Antenna (Nr = 1) 86 4.1.1.2 Arbitrary Number of Receive Antennas (Nr) 88 4.1.1.3 Asymptotic Analysis 89 4.1.2 SM and SSK in the Presence of Imperfect Channel Estimation 90 4.1.2.1 Single Receive Antenna (Nr = 1) 91 4.1.2.2 Arbitrary Number of Receive Antennas (Nr) 92 4.1.2.3 Asymptotic Analysis 92 4.1.3 QSM with Perfect Channel Knowledge at the Receiver 94 4.1.4 QSM in the Presence of Imperfect Channel Estimation 96 4.2 A General Framework for SMTs Average Error Probability over Generalized Fading Channels and in the Presence of Spatial Correlation and Imperfect Channel Estimation 98 4.3 Average Error Probability Analysis of Differential SMTs 101 4.4 Comparative Average Bit Error Rate Results 103 4.4.1 SMTs, GSMTs, and QSMTs ABER Comparisons 103 4.4.2 Differential SMTs Results 107 5 Information Theoretic Treatment for SMTs 109 5.1 Evaluating the Mutual Information 110 5.1.1 Classical SpatialMultiplexing MIMO 110 5.1.2 SMTs 111 5.2 Capacity Analysis 114 5.2.1 SMX 114 5.2.2 SMTs 115 5.2.2.1 Classical SMTs Capacity Analysis 115 5.2.2.2 SMTs Capacity Analysis by Maximing over Spatial and Constellation Symbols 119 5.3 Achieving SMTs Capacity 121 5.3.1 SSK 121 5.3.2 SM 124 5.4 Information Theoretic Analysis in the Presence of Channel Estimation Errors 128 5.4.1 Evaluating the Mutual Information 128 5.4.1.1 Classical SpatialMultiplexing MIMO 128 5.4.1.2 SMTs 129 5.4.2 Capacity Analysis 131 5.4.2.1 SpatialMultiplexing MIMO 131 5.4.2.2 SMTs 134 5.4.3 Achieving SMTs Capacity 135 5.4.3.1 SSK 135 5.4.3.2 SM 136 5.5 Mutual Information Performance Comparison 138 6 Cooperative SMTs 141 6.1 Amplify and Forward (AF) Relaying 141 6.1.1 Average Error Probability Analysis 143 6.1.1.1 Asymptotic Analysis 147 6.1.1.2 Numerical Results 147 6.1.2 Opportunistic AF Relaying 149 6.1.2.1 Average Error Probability Analysis 151 6.1.2.2 Asymptotic Analysis 152 6.2 Decode and Forward (DF) Relaying 152 6.2.1 Multiple single-antenna DF relays 152 6.2.2 Single DF Relay with Multiple Antennas 153 6.2.3 Average Error Potability Analysis 154 6.2.3.1 Multiple Single-Antenna DF Relays 154 6.2.3.2 Single DF Relay with Multiple-Antennas 157 6.2.3.3 Numerical Results 157 6.3 Two-Way Relaying (2WR) SMTs 158 6.3.1 The Transmission Phase 159 6.3.2 The Relaying Phase 161 6.3.3 Average Error Probability Analysis 162 6.3.3.1 Numerical Results 165 7 SMTs for Millimeter-Wave Communications 167 7.1 Line of Sight mmWave Channel Model 168 7.1.1 Capacity Analysis 168 7.1.1.1 SM 168 7.1.1.2 QSM 169 7.1.1.3 Randomly Spaced Antennas 169 7.1.1.4 Capacity Performance Comparison 172 7.1.2 Average Bit Error Rate Results 174 7.2 Outdoor Millimeter-Wave Communications 3D Channel Model 175 7.2.1 Capacity Analysis 179 7.2.2 Average Bit Error Rate Results 182 8 Summary and Future Directions 185 8.1 Summary 185 8.2 Future Directions 187 8.2.1 SMTs with Reconfigurable Antennas (RAs) 187 8.2.2 Practical Implementation of SMTs 188 8.2.3 Index Modulation and SMTs 188 8.2.4 SMTs for OpticalWireless Communications 189 A MatlabCodes 191 A.1 Generating the Constellation Diagrams 191 A.1.1 SSK 191 A.1.2 GSSK 192 A.1.3 SM 193 A.1.4 GSM 194 A.1.5 QSSK 195 A.1.6 QSM 196 A.1.7 GQSSK 197 A.1.8 GQSM 199 A.1.9 SMTs 200 A.1.10 DSSK 202 A.1.11 DSM 203 A.1.12 DSMTs 204 A.2 Receivers 205 A.2.1 SMTs ML Receiver 205 A.2.2 DSMTs ML Receiver 206 A.3 Analytical and Simulated ABER 207 A.3.1 ABER of SM over Rayleigh Fading Channels with No CSE 207 A.3.2 ABER of SM over Rayleigh Fading Channels with CSE 209 A.3.3 ABER of QSM over Rayleigh Fading Channels with No CSE 211 A.3.4 ABER of QSM over Rayleigh Fading Channels with CSE 214 A.3.5 Analytical ABER of SMTs over Generalized Fading Channels and with CSE and SC 216 A.3.6 Simulated ABER of SMTs Using Monte Carlo Simulation over Generalized Fading Channels and with CSE and SC 222 A.3.7 Analytical ABER of DSMTs over Generalized Fading Channels 228 A.3.8 Simulated ABER of DSMTs Using Monte Carlo Simulation over Generalized Fading Channels 232 A.4 Mutual Information and Capacity 235 A.4.1 SMTs Simulated Mutual Information over Generalized Fading Channels and with CSE 235 A.4.2 SMTs Capacity 240 References 243 Index 265

Read more less

Book SynopsisAn important resource that examines the physical aspects of wireless communications based on mathematical and physical evidence The Physics and Mathematics of Electromagnetic Wave Propagation in Cellular Wireless Communicationdescribes the electromagnetic principles for designing a cellular wireless system and includes the subtle electromagnetic principles that are often overlooked in designing such a system. This important text explores both the physics and mathematical concepts used in deploying antennas for transmission and reception of electromagnetic signals and examines how to select the proper methodology from a wide range of scenarios. In this much-needed guide, the authorsnoted experts in the fieldexplore the principle of electromagnetics as developed through the Maxwellian principles and describe the properties of an antenna in the frequency domain. The text also includes a review of the characterization of propagation path loss in a cellular wireless environment and examiTable of ContentsPreface xi Acknowledgments xvii 1 The Mystery of Wave Propagation and Radiation from an Antenna 1 Summary 1 1.1 Historical Overview of Maxwell’s Equations 3 1.2 Review of Maxwell–Hertz–Heaviside Equations 5 1.2.1 Faraday’s Law 5 1.2.2 Generalized Ampere’s Law 8 1.2.3 Gauss’s Law of Electrostatics 9 1.2.4 Gauss’s Law of Magnetostatics 10 1.2.5 Equation of Continuity 11 1.3 Development of Wave Equations 12 1.4 Methodologies for the Solution of the Wave Equations 16 1.5 General Solution of Maxwell’s Equations 19 1.6 Power (Correlation) Versus Reciprocity (Convolution) 24 1.7 Radiation and Reception Properties of a Point Source Antenna in Frequency and in Time Domain 28 1.7.1 Radiation of Fields from Point Sources 28 1.7.1.1 Far Field in Frequency Domain of a Point Radiator 29 1.7.1.2 Far Field in Time Domain of a Point Radiator 30 1.7.2 Reception Properties of a Point Receiver 31 1.8 Radiation and Reception Properties of Finite‐Sized Dipole‐Like Structures in Frequency and in Time 33 1.8.1 Radiation Fields from Wire‐Like Structures in the Frequency Domain 33 1.8.2 Radiation Fields from Wire‐Like Structures in the Time Domain 34 1.8.3 Induced Voltage on a Finite‐Sized Receive Wire‐Like Structure Due to a Transient Incident Field 34 1.8.4 Radiation Fields from Electrically Small Wire‐Like Structures in the Time Domain 35 1.9 An Expose on Channel Capacity 44 1.9.1 Shannon Channel Capacity 47 1.9.2 Gabor Channel Capacity 51 1.9.3 Hartley‐Nyquist‐Tuller Channel Capacity 53 1.10 Conclusion 56 References 57 2 Characterization of Radiating Elements Using Electromagnetic Principles in the Frequency Domain 61 Summary 61 2.1 Field Produced by a Hertzian Dipole 62 2.2 Concept of Near and Far Fields 65 2.3 Field Radiated by a Small Circular Loop 68 2.4 Field Produced by a Finite‐Sized Dipole 70 2.5 Radiation Field from a Finite‐Sized Dipole Antenna 72 2.6 Maximum Power Transfer and Efficiency 74 2.6.1 Maximum Power Transfer 75 2.6.2 Analysis Using Simple Circuits 77 2.6.3 Computed Results Using Realistic Antennas 81 2.6.4 Use/Misuse of the S‐Parameters 84 2.7 Radiation Efficiency of Electrically Small Versus Electrically Large Antenna 85 2.7.1 What is an Electrically Small Antenna (ESA)? 86 2.7.2 Performance of Electrically Small Antenna Versus Large Resonant Antennas 86 2.8 Challenges in Designing a Matched ESA 90 2.9 Near‐ and Far‐Field Properties of Antennas Deployed Over Earth 94 2.10 Use of Spatial Antenna Diversity 100 2.11 Performance of Antennas Operating Over Ground 104 2.12 Fields Inside a Dielectric Room and a Conducting Box 107 2.13 The Mathematics and Physics of an Antenna Array 120 2.14 Does Use of Multiple Antennas Makes Sense? 123 2.14.1 Is MIMO Really Better than SISO? 132 2.15 Signal Enhancement Methodology Through Adaptivity on Transmit Instead of MIMO 138 2.16 Conclusion 148 Appendix 2A Where Does the Far Field of an Antenna Really Starts Under Different Environments? 149 Summary 149 2A.1 Introduction 150 2A.2 Derivation of the Formula 2D2/λ 153 2A.3 Dipole Antennas Operating in Free Space 157 2A.4 Dipole Antennas Radiating Over an Imperfect Ground 162 2A.5 Epilogue 164 References 167 3 Mechanism of Wireless Propagation: Physics, Mathematics, and Realization 171 Summary 171 3.1 Introduction 172 3.2 Description and Analysis of Measured Data on Propagation Available in the Literature 173 3.3 Electromagnetic Analysis of Propagation Path Loss Using a Macro Model 184 3.4 Accurate Numerical Evaluation of the Fields Near an Earth–Air Interface 190 3.5 Use of the Numerically Accurate Macro Model for Analysis of Okumura et al.’s Measurement Data 192 3.6 Visualization of the Propagation Mechanism 199 3.7 A Note on the Conventional Propagation Models 203 3.8 Refinement of the Macro Model to Take Transmitting Antenna’s Electronic and Mechanical Tilt into Account 207 3.9 Refinement of the Data Collection Mechanism and its Interpretation Through the Definition of the Proper Route 210 3.10 Lessons Learnt: Possible Elimination of Slow Fading and a Better Way to Deploy Base Station Antennas 217 3.10.1 Experimental Measurement Setup 224 3.11 Cellular Wireless Propagation Occurs Through the Zenneck Wave and not Surface Waves 227 3.12 Conclusion 233 Appendix 3A Sommerfeld Formulation for a Vertical Electric Dipole Radiating Over an Imperfect Ground Plane 234 Appendix 3B Asymptotic Evaluation of the Integrals by the Method of Steepest Descent 247 Appendix 3C Asymptotic Evaluation of the Integrals When there Exists a Pole Near the Saddle Point 252 Appendix 3D Evaluation of Fields Near the Interface 254 Appendix 3E Properties of a Zenneck Wave 258 Appendix 3F Properties of a Surface Wave 259 References 261 4 Methodologies for Ultrawideband Distortionless Transmission/ Reception of Power and Information 265 Summary 265 4.1 Introduction 266 4.2 Transient Responses from Differently Sized Dipoles 268 4.3 A Travelling Wave Antenna 276 4.4 UWB Input Pulse Exciting a Dipole of Different Lengths 279 4.5 Time Domain Responses of Some Special Antennas 281 4.5.1 Dipole Antennas 281 4.5.2 Biconical Antennas 292 4.5.3 TEM Horn Antenna 299 4.6 Two Ultrawideband Antennas of Century Bandwidth 305 4.6.1 A Century Bandwidth Bi‐Blade Antenna 306 4.6.2 Cone‐Blade Antenna 310 4.6.3 Impulse Radiating Antenna (IRA) 313 4.7 Experimental Verification of Distortionless Transmission of Ultrawideband Signals 315 4.8 Distortionless Transmission and Reception of Ultrawideband Signals Fitting the FCC Mask 327 4.8.1 Design of a T‐pulse 329 4.8.2 Synthesis of a T‐pulse Fitting the FCC Mask 331 4.8.3 Distortionless Transmission and Reception of a UWB Pulse Fitting the FCC Mask 332 4.9 Simultaneous Transmission of Information and Power in Wireless Antennas 338 4.9.1 Introduction 338 4.9.2 Formulation and Optimization of the Various Channel Capacities 342 4.9.2.1 Optimization for the Shannon Channel Capacity 342 4.9.2.2 Optimization for the Gabor Channel Capacity 344 4.9.2.3 Optimization for the Hartley‐Nyquist‐Tuller Channel Capacity 345 4.9.3 Channel Capacity Simulation of a Frequency Selective Channel Using a Pair of Transmitting and Receiving Antennas 347 4.9.4 Optimization of Each Channel Capacity Formulation 353 4.10 Effect of Broadband Matching in Simultaneous Information and Power Transfer 355 4.10.1 Problem Description 357 4.10.1.1 Total Channel Capacity 358 4.10.1.2 Power Delivery 361 4.10.1.3 Limitation on VSWR 361 4.10.2 Design of Matching Networks 362 4.10.2.1 Simplified Real Frequency Technique (SRFT) 362 4.10.2.2 Use of Non‐Foster Matching Networks 366 4.10.3 Performance Gain When Using a Matching Network 367 4.10.3.1 Constraints of VSWR < 2 367 4.10.3.2 Constraints of VSWR < 3 369 4.10.3.3 Without VSWR Constraint 371 4.10.3.4 Discussions 372 4.10.4 PCB (Printed Circuit Board) Implementation of a Broadband‐ Matched Dipole 373 4.11 Conclusion 376 References 377 Index 383

Read more less

Book SynopsisA comprehensive overview of the Internet of Things' core concepts, technologies, and applications Internet of Things A to Z offers a holistic approach to the Internet of Things (IoT) model. The Internet of Things refers to uniquely identifiable objects and their virtual representations in an Internet-like structure. Recently, there has been a rapid growth in research on IoT communications and networks, that confirms the scalability and broad reach of the core concepts. With contributions from a panel of international experts, the text offers insight into the ideas, technologies, and applications of this subject. The authors discuss recent developments in the field and the most current and emerging trends in IoT. In addition, the text is filled with examples of innovative applications and real-world case studies. Internet of Things A to Z fills the need for an up-to-date volume on the topic. This important book: Covers in great detail tTable of ContentsPreface xix Acknowledgments xxv Contributors xxvii Part I Concepts and Perspectives 1 1 Introduction to the Internet of Things 3Detlef Schoder 1.1 Introduction 3 1.2 Internet of Things Concepts 7 1.3 Who Works on the Internet of Things? 11 1.4 Internet of Things Framework 12 1.5 Information and Communication Technology Infrastructure 14 1.6 Derived Qualities of Modern ICT 31 1.7 Potential for Product, Process, and Business Model Innovations 34 1.8 Implications and Challenges 38 1.9 Conclusion 44 2 Environment, People, and Time as Factors in the Internet of Things Technical Revolution 51Jan Sliwa 2.1 Introduction 51 2.2 Technical Revolutions 52 2.3 Cyber–Physical–Social Systems 54 2.4 Environment 56 2.5 Time 58 2.6 People 63 2.7 Cybersecurity 67 2.8 Reasoning from Data 69 2.9 Adaptable Self-Organizing Systems 70 2.10 Moral Things 72 2.11 Conclusion 74 Part II Enablers 77 3 An Overview of Enabling Technologies for the Internet of Things 79Faisal Alsubaei, Abdullah Abuhussein, and Sajjan Shiva 3.1 Introduction 79 3.2 Overview of IoT Architecture 80 3.3 Enabling Technologies 81 3.4 IoT Platforms and Operating Systems 105 3.5 Conclusion 108 4 Cloud and Fog Computing in the Internet of Things 113Daniel Happ 4.1 Introduction 113 4.2 IoT System Requirements 114 4.3 Cloud Computing in IoT 116 4.4 Fog Computing in IoT 122 4.5 Conclusion 131 5 RFID in the Internet of Things 135Akaa Agbaeze Eteng, Sharul Kamal Abdul Rahim, and Chee Yen Leow 5.1 Introduction 135 5.2 Historical Perspective 135 5.3 RFID and the Internet of Things 137 5.4 Emergent Issues 144 5.5 Conclusion 146 6 A Tutorial Introduction to IoT Design and Prototyping with Examples 153Manuel Meruje, Musa Gwani Samaila, Virginia N. L. Franqueira, Mário Marques Freire, and Pedro Ricardo Morais Inácio 6.1 Introduction 153 6.2 Main Features of IoT Hardware Development Platforms 154 6.3 Design and Prototyping of IoT Applications 169 6.4 Projects on IoT Applications 173 6.5 Conclusion 184 7 On Standardizing the Internet of Things and Its Applications 191Kai Jakobs 7.1 Introduction 191 7.2 Current Status 193 7.3 The Standardization Environment 199 7.4 Standardization in Selected Application Areas 201 7.5 Discussion and Some Speculation 210 7.6 Conclusion 213 Part III Security Issues and Solutions 219 8 Security Mechanisms and Technologies for Constrained IoT Devices 221Marco Tiloca and Shahid Raza 8.1 Introduction 221 8.2 Security in IoT Protocols and Technologies 222 8.3 Security Issues and Solutions 234 8.4 Conclusion 247 9 Blockchain-Based Security Solutions for IoT Systems 255Göran Pulkkis, Jonny Karlsson, and Magnus Westerlund 9.1 Introduction 255 9.2 Regulatory Requirements 256 9.3 Blockchain Technology 259 9.4 Blockchains and IoT Systems 261 9.5 Examples of Blockchain-Based Security Solutions for IoT Systems 262 9.6 Challenges and Future Research 270 9.7 Conclusions 270 10 The Internet of Things and IT Auditing 275John Shu, Jason M. Rosenberg, Shambhu Upadhyaya, and Hejamadi Raghav Rao 10.1 Introduction 275 10.2 Risks Associated with IoT 276 10.3 IT Auditing 279 10.4 Use Cases of IoT in IT Auditing 286 10.5 Protecting the Business Network 287 10.6 Conclusion 289 Part IV Application Domains 293 11 The Industrial Internet of Things 295Alexander Willner 11.1 Introduction 295 11.2 Market Overview 296 11.3 Interoperability and Technologies 303 11.4 Alliances 309 11.5 Conclusions 314 12 Internet of Things Applications for Smart Cities 319Daniel Minoli and Benedict Occhiogrosso 12.1 Introduction 319 12.2 IoT Applications for Smart Cities 321 12.3 Specific Smart City Applications 330 12.4 Optimal Enablement of Video and Multimedia Capabilities in IOT 338 12.5 Key Underlying Technologies for Smart Cities IOT Applications 340 12.6 Challenges and Future Research 349 12.7 Conclusion 350 13 Smart Connected Homes 359Joseph Bugeja, Andreas Jacobsson, and Paul Davidsson 13.1 Introduction 359 13.2 The Smart Connected Home Domain 360 13.3 Smart Connected Home Systems 364 13.4 The Smart Connected Home Technologies 367 13.5 Smart Connected Home Architectures 375 13.6 Smart Connected Home Challenges and Research Directions 376 13.7 Conclusions 381 14 The Emerging “Energy Internet of Things” 385Daniel Minoli and Benedict Occhiogrosso 14.1 Introduction 385 14.2 Power Management Trends and EIoT Support 390 14.3 Real-Life Power Management Optimization Approaches 410 14.4 Challenges and Future Directions 415 14.5 Conclusion 417 15 Implementing the Internet of Things for Renewable Energy 425Lucas Finco and Daniel Minoli 15.1 Introduction 425 15.2 Managing the Impact of Sustainable Energy 426 15.3 EIoT Deployment 432 15.4 Industry Standards for EIoT 439 15.5 Security Considerations in EIoT and Clean Energy Environments 441 15.6 Conclusion 442 16 The Internet of Things and People in Health Care 447Nancy L. Russo and Jeanette Eriksson 16.1 Introduction 447 16.2 The Smart Health Care Ecosystem 448 16.3 Dimensions of Internet of Things Applications in Health Care 453 16.4 Examples of IoT-Related Health Care Applications and Their Dimensions 458 16.5 Challenges 469 16.6 Conclusion 471 17 Internet of Things in Smart Ambulance and Emergency Medicine 475Bernard Fong, A. C. M. Fong, and C. K. Li 17.1 Introduction 475 17.2 IoT in Emergency Medicine 477 17.3 Integration and Compatibility 486 17.4 Case Study: Chronic Obstructive Pulmonary Disease 492 17.5 Smart Ambulance Challenges 498 17.6 Conclusions 500 18 Internet of Things Applications for Agriculture 507Lei Zhang, Ibibia K. Dabipi, and Willie L. Brown Jr. 18.1 Introduction 507 18.2 Internet of Things-Based Precision Agriculture 510 18.3 IoT Application in Agriculture Irrigation 512 18.4 IoT Application in Agriculture Fertilization 516 18.5 IoT Application in Crop Disease and Pest Management 518 18.6 IoT Application in Precision Livestock Farming 519 18.7 Conclusion 522 19 The Internet of Flying Things 529Daniel Fernando Pigatto, Mariana Rodrigues, João Vitor de Carvalho Fontes, Alex Sandro Roschildt Pinto, James Smith, and Kalinka Regina Lucas Jaquie Castelo Branco 19.1 Introduction 529 19.2 Flying Things 530 19.3 The Internet of Flying Things 533 19.4 Challenges 542 19.5 Case Studies 549 19.6 Conclusions 557 Part V Relevant Sample Applications 563 20 An Internet of Things Approach to “Read” the Emotion of Children with Autism Spectrum Disorder 565Tiffany Y. Tang and Pinata Winoto 20.1 Introduction 565 20.2 Background 567 20.3 Related Work 568 20.4 The Internet of Things Environment for Emotion Recognition 571 20.5 The Study and Discussions 580 20.6 Conclusions 586 21 A Low-Cost IoT Framework for Landslide Prediction and Risk Communication 593Pratik Chaturvedi, Kamal Kishore Thakur, Naresh Mali, Venkata Uday Kala, Sudhakar Kumar, Srishti Yadav, and Varun Dutt 21.1 Introduction 593 21.2 Background 594 21.3 System Design and Implementation 595 21.4 Testing the IoT Framework 596 21.5 Results 603 21.6 Conclusions 605 Glossary 611 Author’s Biography 625 Index 645

Read more less

Book SynopsisOffers comprehensive insight into the theory, models, and techniques of ultra-dense networks and applications in 5G and other emerging wireless networks The need for speedand powerin wireless communications is growing exponentially. Data rates are projected to increase by a factor of ten every five yearsand with the emerging Internet of Things (IoT) predicted to wirelessly connect trillions of devices across the globe, future mobile networks (5G) will grind to a halt unless more capacity is created. This book presents new research related to the theory and practice of all aspects of ultra-dense networks, covering recent advances in ultra-dense networks for 5G networks and beyond, including cognitive radio networks, massive multiple-input multiple-output (MIMO), device-to-device (D2D) communications, millimeter-wave communications, and energy harvesting communications. Clear and concise throughout, Ultra-Dense Networks for 5G and Beyond - Modelling, Analysis, Table of ContentsList of Contributors xi Preface xv Part I Fundamentals of Ultra-dense Networks 1 1 Fundamental Limits of Ultra-dense Networks 3Marios Kountouris and Van Minh Nguyen 1.1 Introduction 3 1.2 System Model 6 1.2.1 Network Topology 6 1.2.2 Wireless Propagation Model 6 1.2.3 User Association 8 1.2.4 Performance Metrics 8 1.3 The Quest for Exact Analytical Expressions 9 1.3.1 Coverage Probability 10 1.3.2 The Effect of LOS Fading 16 1.3.3 The Effect of BS Height 19 1.4 The Quest for Scaling Laws 25 1.4.1 User Performance 26 1.4.2 Network Performance 33 1.4.3 Network Ordering and Design Guidelines 35 1.5 Conclusions and Future Challenges 36 Bibliography 37 2 Performance Analysis of Dense Small Cell Networks with Line of Sight and Non-Line of Sight Transmissions under Rician Fading 41Amir Hossein Jafari,Ming Ding and David López-Pérez 2.1 Introduction 41 2.2 System Model 42 2.2.1 BS Distribution 42 2.2.2 User Distribution 42 2.2.3 Path Loss 43 2.2.4 User Association Strategy (UAS) 44 2.2.5 Antenna Radiation Pattern 44 2.2.6 Multi-path Fading 44 2.3 Coverage Probability Analysis Based on the Piecewise Path Loss Model 44 2.4 Study of a 3GPP Special Case 46 2.4.1 The Computation of T1L 47 2.4.2 The Computation of T1NL 48 2.4.3 The Computation of T2 L 51 2.4.4 The Computation of T2 NL 51 2.4.5 The Results of pcov(𝜆, 𝛾) and AASE(𝜆, 𝛾0) 52 2.5 Simulation and Discussion 52 2.5.1 Validation of the Analytical Results of pcov(𝜆, 𝛾) for the 3GPP Case 52 2.5.2 Discussion on the Analytical Results of AASE(𝜆, 𝛾0) for the 3GPP Case 54 2.6 Conclusion 55 Appendix A: Proof ofTheorem 1.1 55 Appendix B: Proof of Lemma 2.2 60 Appendix C: Proof of Lemma 2.3 61 Appendix D: Proof of Lemma 2.4 62 Bibliography 62 3 Mean Field Games for 5G Ultra-dense Networks: A Resource Management Perspective 65Mbazingwa E.Mkiramweni, Chungang Yang and Zhu Han 3.1 Introduction 65 3.2 Literature Review 67 3.2.1 5G Ultra-dense Networks 67 3.2.2 Resource Management Challenges in 5G 71 3.2.3 Game Theory for Resource Management in 5G 71 3.3 Basics of Mean field game 71 3.3.1 Background 72 3.3.2 Mean Field Games 73 3.4 MFGs for D2D Communications in 5G 76 3.4.1 Applications of MFGs in 5G Ultra-dense D2D Networks 76 3.4.2 An Example of MFGs for Interference Management in UDN 77 3.5 MFGs for Radio Access Network in 5G 78 3.5.1 Application of MFGs for Radio Access Network in 5G 79 3.5.2 Energy Harvesting 81 3.5.3 An Example of MFGs for Radio Access Network in 5G 81 3.6 MFGs in 5G Edge Computing 84 3.6.1 MFG Applications in Edge Cloud Communication 85 3.7 Conclusion 85 Bibliography 85 Part II Ultra-dense Networks with Emerging 5G Technologies 91 4 Inband Full-duplex Self-backhauling in Ultra-dense Networks 93Dani Korpi, Taneli Riihonen and Mikko Valkama 4.1 Introduction 93 4.2 Self-backhauling in Existing Literature 94 4.3 Self-backhauling Strategies 95 4.3.1 Half-duplex Base Station without Access Nodes 97 4.3.2 Half-duplex Base Station with Half-duplex Access Nodes 97 4.3.3 Full-Duplex Base Station with Half-Duplex Access Nodes 98 4.3.4 Half-duplex Base Station with Full-duplex Access Nodes 99 4.4 Transmit Power Optimization under QoS Requirements 99 4.5 Performance Analysis 101 4.5.1 Simulation Setup 101 4.5.2 Numerical Results 103 4.6 Summary 109 Bibliography 110 5 The Role of Massive MIMO and Small Cells in Ultra-dense Networks 113Qi Zhang, Howard H. Yang and Tony Q. S. Quek 5.1 Introduction 113 5.2 System Model 115 5.2.1 Network Topology 115 5.2.2 Propagation Environment 116 5.2.3 User Association Policy 117 5.3 Average Downlink Rate 117 5.3.1 Association Probabilities 117 5.3.2 Uplink Training 119 5.3.3 Downlink Data Transmission 120 5.3.4 Approximation of Average Downlink Rate 121 5.4 Numerical Results 123 5.4.1 Validation of Analytical Results 123 5.4.2 Comparison between Massive MIMO and Small Cells 124 5.4.3 Optimal Network Configuration 126 5.5 Conclusion 127 Appendix 128 A.1 Proof of Theorem 5.1 128 A.2 Proof of Corollary 5.1 129 A.3 Proof of Theorem 5.2 129 A.4 Proof of Theorem 5.3 130 A.5 Proof of Proposition 5.1 130 A.6 Proof of Proposition 5.2 130 Bibliography 131 6 Security for Cell-free Massive MIMO Networks 135Tiep M. Hoang, Hien Quoc Ngo, Trung Q. Duong and Hoang D. Tuan 6.1 Introduction 135 6.2 Cell-free Massive MIMO System Model 136 6.3 Cell-free System Model in the presence of an active eavesdropper 139 6.4 On Dealing with Eavesdropper 143 6.4.1 Case 1: Power Coefficients Are Different 143 6.4.2 Case 2: Power Coefficients Are the Same 145 6.5 Numerical Results 146 6.6 Conclusion 148 Appendix 149 Bibliography 150 7 Massive MIMO for High-performance Ultra-dense Networks in the Unlicensed Spectrum 151Adrian Garcia-Rodriguez, Giovanni Geraci, Lorenzo Galati-Giordano and David López-Pérez 7.1 Introduction 151 7.2 System Model 152 7.3 Fundamentals of Massive MIMO Unlicensed (mMIMO-U) 154 7.3.1 Channel Covariance Estimation 154 7.3.2 Enhanced Listen Before Talk (eLBT) 155 7.3.3 Neighboring-Node-Aware Scheduling 157 7.3.4 Acquisition of Channel State Information 159 7.3.5 Beamforming with Radiation Nulls 160 7.4 Performance Evaluation 160 7.4.1 Outdoor Deployments 160 7.4.1.1 Cellular/Wi-Fi Coexistence 161 7.4.1.2 Achievable Cellular Data Rates 162 7.4.2 Indoor Deployments 165 7.4.2.1 Channel Access Success Rate 166 7.4.2.2 Downlink User SINR 166 7.4.2.3 Downlink Sum Throughput 169 7.5 Challenges 170 7.5.1 Wi-Fi Channel Subspace Estimation 170 7.5.2 Uplink Transmission 170 7.5.3 Hidden Terminals 171 7.6 Conclusion 172 Bibliography 172 8 Energy Efficiency Optimization for Dense Networks 175Quang-Doanh Vu, Markku Juntti, Een-Kee Hong and Le-Nam Tran 8.1 Introduction 175 8.2 Energy Efficiency Optimization Tools 176 8.2.1 Fractional Programming 176 8.2.2 Concave Fractional Programs 177 8.2.2.1 Parameterized Approach 177 8.2.2.2 Parameter-free Approach 178 8.2.3 Max–Min Fractional Programs 179 8.2.4 Generalized Non-convex Fractional Programs 179 8.2.5 Alternating Direction Method of Multipliers for Distributed Implementation 180 8.3 Energy Efficiency Optimization for Dense Networks: Case Studies 181 8.3.1 Multiple Radio Access Technologies 181 8.3.1.1 System Model and Energy Efficiency Maximization Problem 182 8.3.1.2 Solution via Parameterized Approach 184 8.3.1.3 Solution via Parameter-free Approach 184 8.3.1.4 Distributed Implementation 185 8.3.1.5 Numerical Examples 189 8.3.2 Dense Small Cell Networks 191 8.3.2.1 System Model 191 8.3.2.2 Centralized Solution via Successive Convex Approximation 193 8.3.2.3 Distributed Implementation 195 8.3.2.4 Numerical Examples 198 8.4 Conclusion 200 Bibliography 200 Part III Applications of Ultra-dense Networks 203 9 Big Data Methods for Ultra-dense Network Deployment 205Weisi Guo,Maria Liakata, GuillemMosquera,Weijie Qi, Jie Deng and Jie Zhang 9.1 Introduction 205 9.1.1 The Economic Case for Big Data in UDNs 205 9.1.2 Chapter Organization 207 9.2 Structured Data Analytics for Traffic Hotspot Characterization 207 9.2.1 Social Media Mapping of Hotspots 207 9.2.2 Community and Cluster Detection 211 9.2.3 Machine Learning for Clustering in Heterogeneous UDNs 213 9.3 Unstructured Data Analytics for Quality-of-Experience Mapping 219 9.3.1 Topic Identification 220 9.3.2 Sentiment 221 9.3.3 Data-Aware Wireless Network (DAWN) 222 9.4 Conclusion 226 Bibliography 227 10 Physical Layer Security for Ultra-dense Networks under Unreliable Backhaul Connection 231Huy T. Nguyen, Nam-Phong Nguyen, Trung Q. Duong andWon-Joo Hwang 10.1 Backhaul Reliability Level and Performance Limitation 232 10.1.1 Outage Probability Analysis under Backhaul Reliability Impacts 233 10.1.2 Performance Limitation 234 10.1.3 Numerical Results 234 10.2 Unreliable Backhaul Impacts with Physical Layer Security 235 10.2.1 The Two-Phase Transmitter/Relay Selection Scheme 237 10.2.2 Secrecy Outage Probability with Backhaul Reliability Impact 240 10.2.3 Secrecy Performance Limitation under Backhaul Reliability Impact 240 10.2.4 Numerical Results 241 Appendix A 242 Appendix B 243 Appendix C 244 Bibliography 245 11 SimultaneousWireless Information and Power Transfer in UDNs with Caching Architecture 247Sumit Gautam, Thang X. Vu, Symeon Chatzinotas and Björn Ottersten 11.1 Introduction 247 11.2 System Model 249 11.2.1 Signal Model 250 11.2.2 Caching Model 251 11.2.3 Power Assumption at the Relay 252 11.3 Maximization of the serving information rate 252 11.3.1 Optimization of TS Factors and the Relay Transmit Power 253 11.3.2 Relay Selection 255 11.4 Maximization of the Energy Stored at the Relay 255 11.4.1 Optimization of TS Factors and the Relay Transmit Power 256 11.4.2 Relay Selection 259 11.5 Numerical Results 260 11.6 Conclusion 263 Acknowledgment 265 Bibliography 265 12 Cooperative Video Streaming in Ultra-dense Networks with D2D Caching 267Nguyen-Son Vo and Trung Q. Duong 12.1 Introduction 267 12.2 5G Network with Dense D2D Caching for Video Streaming 268 12.2.1 System Model and Assumptions 269 12.2.2 Cooperative Transmission Strategy 270 12.2.3 Source Video Packetization Model 271 12.3 Problem Formulation and Solution 273 12.3.1 System Parameters Formulation 273 12.3.1.1 Average Reconstructed Distortion 273 12.3.1.2 Energy Consumption Guarantee 274 12.3.1.3 Co-channel Interference Guarantee 275 12.3.2 RDO Problem 275 12.3.3 GAs Solution 276 12.4 Performance Evaluation 276 12.4.1 D2D Caching 276 12.4.2 RDO 277 12.4.2.1 Simulation Setup 277 12.4.2.2 Performance Metrics 280 12.4.2.3 Discussions 285 12.5 Conclusion 285 Bibliography 285 Index 289

Read more less

Book SynopsisA practicing engineer''s inclusive review of communication systems based on shared-bus and shared-memory switch/router architectures This book delves into the inner workings of router and switch design in a comprehensive manner that is accessible to a broad audience. It begins by describing the role of switch/routers in a network, then moves on to the functional composition of a switch/router. A comparison of centralized versus distributed design of the architecture is also presented. The author discusses use of bus versus shared-memory for communication within a design, and also covers Quality of Service (QoS) mechanisms and configuration tools. Written in a simple style and language to allow readers to easily understand and appreciate the material presented, Switch/Router Architectures: Shared-Bus and Shared-Memory Based Systems discusses the design of multilayer switchesstarting with the basic concepts and on to the basic architectures. It describes thTable of ContentsAbout the Author vii Preface ix 1 Introduction to Switch/Router Architectures 1 2 Understanding Shared-Bus and Shared-Memory Switch Fabrics 17 3 Shared-Bus and Shared-Memory-Based Switch/Router Architectures 43 4 Software Requirements for Switch/Routers 61 5 Architectures with Bus-Based Switch Fabrics: Case Study-DECNIS 500/600 Multiprotocol Bridge/Router 87 6 Architectures with Bus-Based Switch Fabrics: Case Study-Fore Systems Powerhub Multilayer Switches 111 7 Architectures with Bus-Based Switch Fabrics: Case Study-Cisco Catalyst 6000 Series Switches 129 8 Architectures with Shared-Memory-Based Switch Fabrics: Case Study-Cisco Catalyst 3550 Series Switches 151 9 Architectures with Bus-Based Switch Fabrics: Case Study-Cisco Catalyst 6500 Series Switches with Supervisor Engine 32 171 10 Architectures with Shared-Memory-Based Switch Fabrics: Case Study-Cisco Catalyst 8500 CSR Series 191 11 Quality of Service Mechanisms in the Switch/Routers 213 12 Quality of Service Configuration Tools in Switch/Routers 227 13 Case Study: Quality of Service Processing in the Cisco Catalyst 6000 and 6500 Series Switches 249 Appendix A: Ethernet Appendix B: IPv4 Packet References Index

Read more less

Book SynopsisA comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author a noted expert on the topic covers a wide range of topics including system architecture anTable of ContentsList of Contributors xv Preface xxi Part I Spectrum Intelligence and Adaptive Resource Management 1 1 Machine Learning for Spectrum Access and Sharing 3Kobi Cohen 1.1 Introduction 3 1.2 Online Learning Algorithms for Opportunistic Spectrum Access 4 1.3 Learning Algorithms for Channel Allocation 9 1.4 Conclusions 19 Acknowledgments 20 Bibliography 20 2 Reinforcement Learning for Resource Allocation in Cognitive Radio Networks 27Andres Kwasinski, Wenbo Wang, and Fatemeh Shah Mohammadi 2.1 Use of Q-Learning for Cross-layer Resource Allocation 29 2.2 Deep Q-Learning and Resource Allocation 33 2.3 Cooperative Learning and Resource Allocation 36 2.4 Conclusions 42 Bibliography 43 3 Machine Learning for Spectrum Sharing in Millimeter-Wave Cellular Networks 45Hadi Ghauch, Hossein Shokri-Ghadikolaei, Gabor Fodor, Carlo Fischione, and Mikael Skoglund 3.1 Background and Motivation 45 3.2 System Model and Problem Formulation 49 3.3 Hybrid Solution Approach 54 3.4 Conclusions and Discussions 59 Appendix A Appendix for Chapter 3 61 A.1 Overview of Reinforcement Learning 61 Bibliography 61 4 Deep Learning–Based Coverage and Capacity Optimization 63Andrei Marinescu, Zhiyuan Jiang, Sheng Zhou, Luiz A. DaSilva, and Zhisheng Niu 4.1 Introduction 63 4.2 Related Machine Learning Techniques for Autonomous Network Management 64 4.3 Data-Driven Base-Station Sleeping Operations by Deep Reinforcement Learning 67 4.4 Dynamic Frequency Reuse through a Multi-Agent Neural Network Approach 72 4.5 Conclusions 81 Bibliography 82 5 Machine Learning for Optimal Resource Allocation 85Marius Pesavento and Florian Bahlke 5.1 Introduction and Motivation 85 5.2 System Model 88 5.3 Resource Minimization Approaches 90 5.4 Numerical Results 96 5.5 Concluding Remarks 99 Bibliography 100 6 Machine Learning in Energy Efficiency Optimization 105Muhammad Ali Imran, Ana Flávia dos Reis, Glauber Brante, Paulo Valente Klaine, and Richard Demo Souza 6.1 Self-Organizing Wireless Networks 106 6.2 Traffic Prediction and Machine Learning 110 6.3 Cognitive Radio and Machine Learning 111 6.4 Future Trends and Challenges 112 6.5 Conclusions 114 Bibliography 114 7 Deep Learning Based Traffic and Mobility Prediction 119Honggang Zhang, Yuxiu Hua, Chujie Wang, Rongpeng Li, and Zhifeng Zhao 7.1 Introduction 119 7.2 Related Work 120 7.3 Mathematical Background 122 7.4 ANN-Based Models for Traffic and Mobility Prediction 124 7.5 Conclusion 133 Bibliography 134 8 Machine Learning for Resource-Efficient Data Transfer in Mobile Crowdsensing 137Benjamin Sliwa, Robert Falkenberg, and Christian Wietfeld 8.1 Mobile Crowdsensing 137 8.2 ML-Based Context-Aware Data Transmission 140 8.3 Methodology for Real-World Performance Evaluation 148 8.4 Results of the Real-World Performance Evaluation 149 8.5 Conclusion 152 Acknowledgments 154 Bibliography 154 Part II Transmission Intelligence and Adaptive Baseband Processing 157 9 Machine Learning–Based Adaptive Modulation and Coding Design 159Lin Zhang and Zhiqiang Wu 9.1 Introduction and Motivation 159 9.2 SL-Assisted AMC 162 9.3 RL-Assisted AMC 172 9.4 Further Discussion and Conclusions 178 Bibliography 178 10 Machine Learning–Based Nonlinear MIMO Detector 181Song-Nam Hong and Seonho Kim 10.1 Introduction 181 10.2 A Multihop MIMO Channel Model 182 10.3 Supervised-Learning-based MIMO Detector 184 10.4 Low-Complexity SL (LCSL) Detector 188 10.5 Numerical Results 191 10.6 Conclusions 193 Bibliography 193 11 Adaptive Learning for Symbol Detection: A Reproducing Kernel Hilbert Space Approach 197Daniyal Amir Awan, Renato Luis Garrido Cavalcante, Masahario Yukawa, and Slawomir Stanczak 11.1 Introduction 197 11.2 Preliminaries 198 11.3 System Model 200 11.4 The Proposed Learning Algorithm 203 11.5 Simulation 207 11.6 Conclusion 208 Appendix A Derivation of the Sparsification Metric and the Projections onto the Subspace Spanned by the Nonlinear Dictionary 210 Bibliography 211 12 Machine Learning for Joint Channel Equalization and Signal Detection 213Lin Zhang and Lie-Liang Yang 12.1 Introduction 213 12.2 Overview of Neural Network-Based Channel Equalization 214 12.3 Principles of Equalization and Detection 219 12.5 Performance of OFDM Systems With Neural Network-Based Equalization 232 12.6 Conclusions and Discussion 236 Bibliography 237 13 Neural Networks for Signal Intelligence: Theory and Practice 243Jithin Jagannath, Nicholas Polosky, Anu Jagannath, Francesco Restuccia, and Tommaso Melodia 13.1 Introduction 243 13.2 Overview of Artificial Neural Networks 244 13.3 Neural Networks for Signal Intelligence 248 13.4 Neural Networks for Spectrum Sensing 255 13.5 Open Problems 259 13.6 Conclusion 260 Bibliography 260 14 Channel Coding with Deep Learning: An Overview 265Shugong Xu 14.1 Overview of Channel Coding and Deep Learning 265 14.2 DNNs for Channel Coding 268 14.3 CNNs for Decoding 277 14.4 RNNs for Decoding 279 14.5 Conclusions 283 Bibliography 283 15 Deep Learning Techniques for Decoding Polar Codes 287Warren J. Gross, Nghia Doan, Elie Ngomseu Mambou, and Seyyed Ali Hashemi 15.1 Motivation and Background 287 15.2 Decoding of Polar Codes: An Overview 289 15.3 DL-Based Decoding for Polar Codes 292 15.4 Conclusions 299 Bibliography 299 16 Neural Network–Based Wireless Channel Prediction 303Wei Jiang, Hans Dieter Schotten, and Ji-ying Xiang 16.1 Introduction 303 16.2 Adaptive Transmission Systems 305 16.3 The Impact of Outdated CSI 307 16.4 Classical Channel Prediction 309 16.5 NN-Based Prediction Schemes 313 16.6 Summary 323 Bibliography 323 Part III Network Intelligence and Adaptive System Optimization 327 17 Machine Learning for Digital Front-End: a Comprehensive Overview 329Pere L. Gilabert, David López-Bueno, Thi Quynh Anh Pham, and Gabriel Montoro 17.1 Motivation and Background 329 17.2 Overview of CFR and DPD 331 17.3 Dimensionality Reduction and ML 341 17.4 Nonlinear Neural Network Approaches 350 17.5 Support Vector Regression Approaches 368 17.6 Further Discussion and Conclusions 373 Bibliography 374 18 Neural Networks for Full-Duplex Radios: Self-Interference Cancellation 383Alexios Balatsoukas-Stimming 18.1 Nonlinear Self-Interference Models 384 18.2 Digital Self-Interference Cancellation 386 18.3 Experimental Results 391 18.4 Conclusions 393 Bibliography 395 19 Machine Learning for Context-Aware Cross-Layer Optimization 397Yang Yang, Zening Liu, Shuang Zhao, Ziyu Shao, and Kunlun Wang 19.1 Introduction 397 19.2 System Model 399 19.3 Problem Formulation and Analytical Framework 402 19.4 Predictive Multi-tier Operations Scheduling (PMOS) Algorithm 409 19.5 A Multi-tier Cost Model for User Scheduling in Fog Computing Networks 413 19.6 Conclusion 420 Bibliography 421 20 Physical-Layer Location Verification by Machine Learning 425Stefano Tomasin, Alessandro Brighente, Francesco Formaggio, and Gabriele Ruvoletto 20.1 IRLV by Wireless Channel Features 427 20.2 ML Classification for IRLV 428 20.3 Learning Phase Convergence 431 20.4 Experimental Results 433 20.5 Conclusions 437 Bibliography 437 21 Deep Multi-Agent Reinforcement Learning for Cooperative Edge Caching 439M. Cenk Gursoy, Chen Zhong, and Senem Velipasalar 21.1 Introduction 439 21.2 System Model 441 21.3 Problem Formulation 443 21.4 Deep Actor-Critic Framework for Content Caching 446 21.5 Application to the Multi-Cell Network 448 21.6 Application to the Single-Cell Network with D2D Communications 452 21.7 Conclusion 454 Bibliography 455 Index 459

Read more less

Book SynopsisIEEE 802.11ba Discover the latest developments in IEEE 802.11ba and Wake-up Radios In IEEE 802.11ba: Ultra-Low Power Wake-up Radio Standard, expert engineers Drs. Steve Shellhammer, Alfred Asterjadhi, and Yanjun Sun deliver a detailed discussion of the IEEE 802.11ba standard. The book begins by explaining the concept of a wake-up radio (WUR) and how it fits into the overall 802.11 standard, as well as how a WUR saves power and extends battery life. The authors go on to describe the medium access control (MAC) layer in detail and then talk about the various protocols used to negotiate WUR operation, its uses for different functionalities (like wake up of the main radio, discovery, synchronization, and security). The book offers a detailed description of the physical (PHY) layer packet construction and the rationale for the design, as well as the various design aspects of the medium access control layer. It also includes: A thorough introduction Table of ContentsAuthor Biography xi 1 Introduction 1 1.1 Background 1 1.2 Overview 3 1.3 Book Outline 5 2 Overview of IEEE 802.11 9 2.1 Introduction 9 2.2 Overview of the IEEE 802.11 PHY Layer 10 2.2.1 Operating Frequencies and Bandwidths 10 2.2.2 Ofdm 11 2.2.3 Ofdm Ppdu 12 2.3 Overview of IEEE 802.11 MAC Layer 16 2.3.1 Network Discovery 16 2.3.2 Connection Setup 18 2.3.3 Coordinated Wireless Medium Access 19 2.3.4 Enhanced Distributed Channel Access 20 2.3.5 Security 20 2.3.6 Time Synchronization 21 2.3.7 Power- Saving Mechanisms 21 2.3.8 Orthogonal Frequency Division Multiple Access (ofdma) 23 2.4 Conclusions 24 References 24 3 Wake- up Radio Concept 25 3.1 Introduction 25 3.2 Primary Sources of Power Consumption in an IEEE 802.11 Station 26 3.2.1 Power Consumption in Transmit Mode 26 3.2.2 Power Consumption in Receive Mode 28 3.2.3 Power Consumption in Sleep Mode 30 3.2.4 Power Consumption in Deep Sleep Mode 30 3.3 Wake- up Radio Concept 31 3.4 Example of Power Consumption Using a Wake- up Radio 37 3.5 Selection of Duty Cycle Values 39 3.6 Conclusions 42 4 Physical Layer Description 43 4.1 Introduction 43 4.2 Requirements 45 4.3 Regulations 47 4.4 Link Budget Considerations 50 4.5 Modulation 53 4.6 Physical Layer Protocol Data Unit (PPDU) Structure 55 4.6.1 Non- WUR Portion of PPDU 55 4.6.2 Sync Field 58 4.6.3 Data Field 61 4.7 Symbol Randomization 62 4.8 FDMA Operation 66 4.8.1 40 MHz FDMA 66 4.8.2 80 MHz FDMA 67 4.9 Additional Topics 67 4.10 Conclusions 68 References 68 5 Physical Layer Performance 73 5.1 Introduction 73 5.2 Generic Non- coherent Receiver 73 5.3 Simulation Description 75 5.3.1 Transmitter Model 76 5.3.2 MC- OOK Symbol Waveform Generation 76 5.3.3 Channel Model 77 5.3.4 Receiver Model 79 5.3.5 Performance Metrics 80 5.4 PHY Performance: Simulation Results 81 5.4.1 Sync Field Detection Rate 82 5.4.2 Sync Field Classification Error Rate 83 5.4.3 Sync Field Timing Error 85 5.4.4 Packet Error Rate 88 5.4.5 Effects of Transmit Diversity 88 5.5 Link Budget Comparison 92 5.5.1 Comparison to the 6 Mb/s OFDM PHY 93 5.5.2 Comparison to the 1 Mb/s Non-OFDM PHY 94 5.6 Conclusions 95 References 95 6 Wake- up Radio Medium Access Control 97 6.1 Introduction 97 6.2 Network Discovery 97 6.2.1 General 97 6.2.2 WUR Discovery 98 6.3 Connectivity and Synchronization 102 6.3.1 General 102 6.3.2 WUR Beacon Frame Generation 102 6.3.3 WUR Beacon Frame Processing 104 6.4 Power Management 105 6.4.1 General 105 6.4.1.1 MR Power Management 105 6.4.1.2 WUR Power Management 106 6.4.2 WUR Modes 108 6.4.2.1 WUR Mode Setup 108 6.4.2.2 WUR Mode Update 110 6.4.2.3 WUR Mode Suspend and Resume 111 6.4.2.4 WUR Mode Teardown 111 6.4.3 Duty Cycle Operation 112 6.4.3.1 WUR Duty Cycle Period 113 6.4.3.2 WUR Duty Cycle Service Period 114 6.4.3.3 WUR Duty Cycle Start Time 114 6.4.4 WUR Wake Up Operation 116 6.4.4.1 Individual DL BU Delivery Context 116 6.4.4.2 Group Addressed DL BU Delivery Context 119 6.4.4.3 Critical BSS Update Delivery Context 121 6.4.5 Use of WUR Short Wake- up Frames 124 6.4.6 Keep Alive Frames 126 6.5 Frequency Division Multiple Access 127 6.6 Protected Wake- up Frames 129 6.7 Conclusion 130 7 Medium Access Control Frame Design 131 7.1 Introduction 131 7.2 Information Elements 131 7.2.1 General 131 7.2.2 Elements Supporting MR Functionalities 132 7.2.2.1 DSSS Parameter Set Element 133 7.2.2.2 EDCA Parameter Set Element 133 7.2.2.3 Channel Switch Announcement Element 135 7.2.2.4 Extended Channel Switch Announcement Element 136 7.2.2.5 HT Operation Element 136 7.2.2.6 VHT Operation Element 137 7.2.2.7 Wide Bandwidth Channel Switch Element 138 7.2.2.8 Channel Switch Wrapper Element 139 7.2.2.9 HE Operation Element 139 7.2.3 Elements Supporting WUR Functionalities 142 7.2.3.1 WUR Capabilities Element 142 7.2.3.2 WUR Operation Element 142 7.2.3.3 WUR Mode Element 145 7.2.3.4 WUR Discovery Element 154 7.2.3.5 WUR PN Update Element 155 7.3 Main Radio MAC Frames 155 7.3.1 Beacon Frame 155 7.3.2 Probe Request/Response Frames 156 7.3.3 (Re)Association Request/Response Frames 156 7.3.4 Action Frames 157 7.4 WUR MAC Frames 157 7.4.1 WUR Beacon Frame 161 7.4.2 WUR Wake- up Frame 161 7.4.3 WUR Discovery Frame 164 7.4.4 WUR Vendor-Specific Frame 165 7.4.5 WUR Short Wake- up Frame 166 7.5 Conclusion 167 Index 169

Read more less

Book SynopsisSMART AND SUSTAINABLE APPROACHES FOR OPTIMIZING PERFORMANCE OF WIRELESS NETWORK Explores the intersection of sustainable growth, green computing and automation, and performance optimization of 5G wireless networks Smart and Sustainable Approaches for Optimizing Performance of Wireless Networks explores how wireless sensing applications, green computing, and Big Data analytics can increase the energy efficiency and environmental sustainability of real-time applications across areas such as healthcare, agriculture, construction, and manufacturing. Bringing together an international team of expert contributors, this authoritative volume highlights the limitations of conventional technologies and provides methodologies and approaches for addressing Quality of Service (QOS) issues and optimizing network performance. In-depth chapters cover topics including blockchain-assisted secure data sharing, smart 5G Internet of Things (IoT) scenarios, intelligent managemeTable of Contents1 Analysis and Clustering of Sensor Recorded Data to Determine Sensors Consuming the Least EnergyPrashant Abbi, Khushi Arora, Praveen Kumar Gupta, K.B. Ashwini, V. Chayapathy, and M.J. Vidya 1.1 Importance of Low Energy Consumption Sensors 1.2 Methodology: Clustering Using K Means and Classification Using KNN 1.3 Objective Realization and Result of Analysis 1.4 Introduction 1.5 Working of WSNs and Sensor Nodes 1.6 Classification of WSNs 1.6.1 Benefits and Drawbacks of Centralized Techniques 1.6.2 Benefits and Drawbacks of Distributed Techniques 1.7 Security Issues 1.7.1 Layering of Level Based Security 1.8 Energy Consumption Issues 1.9 Commonly Used Standards and Protocols for WSNs 1.9.1 Slotted Protocols 1.9.1.1 Time Division Multiple Access 1.9.1.2 Zig Bee/801.15.4 1.9.1.3 Sensor Medium Access Control 1.10 Effects of Temperature and Humidity on the Energy of WSNs 1.10.1 Effects of Temperature on Signal Strength 1.10.2 Effects of Humidity on Signal Strength 1.10.3 Temperature Vs. Humidity 1.11 Proposed Methodology 1.11.1 Information Gathering and Analysis 1.11.2 System Design and Implementation 1.11.3 Testing and Evaluation 1.12 Conclusion References 2 Impact of Artificial Intelligence in Designing of 5GK. Maheswari, Mohankumar, and Banuroopa 2.1 5G – An Introduction 2.1.1 Industry Applications 2.1.2 Healthcare 2.1.3 Retail 2.1.4 Agriculture 2.1.5 Manufacturing 2.1.6 Logistics 2.1.7 Sustainability of 5G Networks 2.1.8 Implementation of 5G 2.1.9 Architecture of 5G Technology 2.2 5G and AI 2.2.1 Gaming and Virtual Reality 2.3 AI and 5G 2.3.1 Continuous Learning AI Model 2.4 Challenges and Roadmap 2.4.1 Technical Issues 2.4.2 Technology Roadmap 2.4.3 Deployment Roadmap 2.5 Mathematical Models 2.5.1 The Insights of Mathematical Modeling in 5G Networks 2.6 Conclusion References 3 Sustainable Paradigm for Computing the Security of Wireless Internet of Things: Blockchain TechnologySana Zeba, Mohammed Amjad, and Danish Raza Rizvi 3.1 Introduction 3.2 Research Background 3.2.1 The Internet of Things 3.2.1.1 Security Requirements in Wireless IoT 3.2.1.2 Layered Architecture of Wireless IoT 3.2.2 Blockchain Technology 3.2.2.1 Types of Blockchain 3.2.2.2 Integration of Blockchain with Wireless Internet of Things 3.3 Related Work 3.3.1 Security Issues in Wireless IoT System 3.3.2 Solutions of Wireless IoT Security Problem 3.4 Research Methodology 3.5 Comparison of Various Existing Solutions 3.6 Discussion of Research Questions 3.7 Future Scope of Blockchain in IoT 3.8 Conclusion References 4 Cognitive IoT Based Health Monitoring Scheme Using Non-Orthogonal MultipleAccessAshiqur Rahman Rahul, Saifur Rahman Sabuj, Majumder Fazle Haider, andShakil Ahmed 4.1 Introduction 4.2 Related Work 4.3 System Model and Implementation 4.3.1 Network Description 4.3.2 Sensing and Transmission Analysis 4.3.3 Pathloss Model 4.3.4 Mathematical Model Evaluation 4.3.4.1 Effectual Throughput 4.3.4.2 Interference Throughput 4.3.4.3 Energy Efficiency 4.3.4.4 Optimum Power 4.3.4.4.1 Optimum Power Derivation for HRC 4.2.3.4.2 Optimum Power Derivation for MRC 4.4 Simulation Results 4.5 Conclusion 4.A Appendices 4.A.1 Proof of Optimum Power Transmission for HRC Device at EffectualState (z = 0) 4.A.2 Proof of Optimum Power Transmission for HRC Device inInterference State (z = 1) 4.A.3 Proof of Optimum Power Transmission for MRC Device at EffectualState (z = 0) 4.A.4 Proof of Optimum Power Transmission for MRC Device inInterference State (z = 1) References 5 Overview of Resource Management for Wireless Adhoc NetworkMehajabeen Fatima and Afreen Khueaheed 5.1 Introduction 5.1.1 Wired and Wireless Network Design Approach 5.1.2 History 5.1.3 Spectrum of Wireless Adhoc Network 5.1.4 Enabling and Networking Technologies 5.1.5 Taxonomy of Wireless Adhoc Network (WANET) 5.2 Mobile Adhoc Network (MANET) 5.2.1 Introduction to MANET 5.2.2 Common Characteristics of MANET 5.2.3 Advantages and Disadvantages 5.2.4 Applications of MANET 5.2.5 Major Issues of MANET 5.3 Vehicular Adhoc Network (VANET) 5.3.1 Introduction of VANET 5.3.2 Common Features of VANET 5.3.3 Pros, Cons, Applications 5.4 Wireless Mesh Network (WMN) 5.4.1 Preface of WMN 5.4.2 Common Traits of WMN 5.4.3 WMN Has Many Open Issues and Research Challenges 5.4.4 Performance Metrics 5.4.5 Advantages and Disadvantages 5.4.6 Prominent Areas and Challenges of WMN 5.5 Wireless Sensor Network (WSN) 5.5.1 Overview of WSN 5.5.2 Common Properties of WSN 5.5.3 Benefits, Harms, and Usage of WSN 5.6 Intelligent Management in WANET 5.6.1 Major Issues of WANET 5.6.2 Challenges of MAC Protocols 5.6.3 Routing Protocols 5.6.3.1 Challenges of Routing Protocols 5.6.3.1.1 Scalability 5.6.3.1.2 Quality of Service 5.6.3.1.3 Security 5.6.4 Energy and Battery Management 5.7 Future Research Directions 5.8 Conclusion References 6 Survey: Brain Tumor Detection Using MRI Image with Deep Learning TechniquesChalapathiraju Kanumuri and C.H. Renu Madhavi 6.1 Introduction 6.2 Background 6.2.1 Types of Medical Imaging 6.2.2 M. R. Imaging as a Modality 6.2.3 Types of Brain Tumor M. R. Imaging Modalities 6.2.4 Suitable Technologies Before Machine Learning 6.2.5 MRI Brain Image Segmentation 6.3 Related Work 6.4 Gaps and Observations 6.5 Suggestions 6.6 Conclusion References 7 Challenges, Standards, and Solutions for Secure and Intelligent 5G Internet of Things (IoT) ScenariosAyasha Malik and Bharat Bhushan 7.1 Introduction 7.2 Safety in Wireless Networks: Since 1G to 4G 7.2.1 Safety in Non-IP Networks 7.2.2 Safety in 3G 7.2.3 Security in 4G 7.2.4 Security in 5G 7.2.4.1 Flashy System Traffic and Radio Visual Security Keys 7.2.4.2 Authorized Network Security and Compliance with Subscriber Level Safety Policies 7.2.5 Security in 5G and Beyond 7.3 IoT Background and Requirements 7.3.1 IoT and Its Characteristics 7.3.2 Characteristics of IoT Infrastructure 7.3.3 Characteristics of IoT Applications 7.3.4 Expected Benefits of IoT Adoption for Organization 7.3.4.1 Benefits Correlated to Big Data Created by IoT 7.3.4.2 Benefits Interrelated to the Openness of IoT 7.3.4.3 BenefitsRelated to the Linked Aspect6 of IoT 7.4 Non 5G Standards Supporting IoT 7.4.1 Bluetooth Low Energy 7.4.2 IEEE 802.15.4 7.4.3 LoRa 7.4.4 Sigfox 7.4.5. WiFi HaLow 7.5 5 G Advanced Security Model 7.5.1 Confidentiality 7.5.2 Integrity 7.5.3 Accessibility 7.5.4 Integrated Safety Rule 7.5.5 Visibility 7.6 Safety Challenges and Resolution of Three-Tiers Structure of 5G Networks 7.6.1 Heterogeneous Access Networks 7.6.1.1 Safety Challengers 7.6.1.2 Safety Resolutions 7.6.2 Backhaul Networks 7.6.2.1 Safety Challenges 7.6.2.2 Safety Resolutions 7.6.3 Core Network 7.6.3.1 Safety Challenges 7.6.3.2 Safety Resolutions 7.7 Conclusion and Future Research Directions References 8 Blockchain Assisted Secure Data Sharing in Intelligent Transportation SystemsGujkan Madaan, Avinash Kumar, and Bharat Bhushan 8.1 Introduction 8.2 Intelligent Transport System 8.2.1 ITS Overview 8.2.2 Issues in ITS 8.2.3 ITS Role in IoT 8.3 Blockchain Technology 8.3.1 Overview 8.3.2 Types of Blockchain 8.3.2.1 Public Blockchain 8.3.2.3 Private Blockchain 8.2.3.2 Federated Blockchain 8.3.3 Consensus Mechanism 8.3.3.1 Proof of Work 8.3.3.2 Proof of Stake 8.3.3.3 Delegated Proof of Stake 8.3.3.4 Practical Byzantine Fault Tolerance 8.3.3.5 Casper 8.3.3.6 Ripple 8.3.3.7 Proof of Activity 8.3.4 Cryptography 8.3.5 Data Management and Its Structure 8.4 Blockchain Assisted Intelligent Transportation System 8.4.1 Security and Privacy 8.4.2 Blockchain and Its Application foe Improving Security and Privacy 8.4.3 ITS Based on Blockchain 8.4.4 Recent Advancement 8.5 Future Research Perspectives 8.5.1 Electric Vehicle Recharging 8.5.2 Smart City Enabling and Smart Vehicle Security 8.5.3 Deferentially-Privacy Preserving Solutions 8.5.4 Distribution of Economic Profits and Incentives 8.6 Conclusion References 9 Utilization of Agro Waste for Energy Engineering Applications: Toward the Manufacturing of Batteries and Super CapacitorsS.N. Kumar, S. Akhil, R.P. Nishita, O. Lijo Joseph, Aju Matthew George, and I Christina Jane 9.1 Introduction 9.2 Super Capacitors and Electrode Materials 9.2.1 Energy Density 9.3 Related Works in the Utilization of Agro Waste for Energy EngineeringApplications 9.4 Inferences from Work Related with Utilization of Coconut. Rice Husk, andPineapple Waste for Fabrication of Super Capacitor 9.5 Factors Contributing in the Fabrication of Super Capacitor from Agro Waste 9.6 Conclusion Acknowledgment References 10 Computational Intelligence Techiques for Optimization in NetworksAshu Gautam and Rashima Mahajan 10.1 Introduction Focussing on Pedagogy of Impending Approach 10.1.1 Security Challenge in Networks 10.1.2 Attacks Vulnerability in Complex Networks 10.2 Relevant Analysis 10.3 Broad Area of Research 10.3.1 Routing Protocols 10.3.2 Hybrid Protocols 10.4 Problem Identification 10.5 Objectives of the Study 10.6 Methodology to be Adopted 10.7 Proposed/Expected Outcome of the Research References 11 R&D Export and ICT Regimes in IndiaZeba, M. Afshar Alam, Harleen Kaur*, Ihtiram Raza Khan, Bhavya AlankarCorresponding Author: Harleen Kaur 11.1 Introduction 11.2 Artificial Intelligence: the Uptake of Infrastructure Development 11.3 Future Analysis and Conclusion References 12 Metaheuristics to Aid Energy-Efficient Path Selection in Route Aggregated Mobile Ad Hoc NetworksDeepa Mehta, Sherin Zafar, Siddhartha Sankar Biswas, Nida Iftekhar, and Samia Khan 12.1 Introduction 12.2 Framework 12.2.1 Route Aggregation 12.3 Clustering 12.4 Ant Colony Optimization 12.4.1 Setting Parameters and Initializing 12.4.2 Generating Solutions 12.4.3 Pheromone Update 12.5 Methodology 12.5.1 Energy Efficient ACO Algorithm 12.5.2 ACO Aided Cluster and Head Selection 12.5.3 ACO Aided Route Aggregation 12.5.4 ACO Aided Energy: Efficient Path Selection 12.6 Results 12.7 Discussion 12.8 Conclusion References 13 Knowledge Analytics in IOMT-MANET Through QoS Optimization for SustainabilityNeha Sharma, Nida Iftekhar, and Samia Khan 13.1 Introduction 13.2 Related Work 13.3 Proposed Neoteric Nature Inspired IWD Algorithm for ZRP 13.4 Simulation Results 13.5 Conclusion and Future Work References 14 Appraise Assortment of IOT Security OptimizationAyesha Hena Afzal and M. Afshar Alam 14.1 Introduction 14.2 Literature Review 14.3 Analysis of Traditional Security Mechanisms in IOT 14.4 Conclusion and Future Scope References 15 Trust Based Hybrid Routing Approach for Securing MANETNeha Sharma and Satrupa Biswas 15.1 Introduction 15.2 Literature Review 15.3 Gaps and Objectives from the Literature Review 15.4 Methodology to be Adopted 15.5 Comparison Analysis 15.6 Conclusion and Future Scope References 16 Study of Security Issues on Open ChannelMd Mudassir Chaudhary, Siddhartha Sankar Biswas, Md Tabrez Nafis, and Safdar Tenweer 16.1 Introduction 16.2 Wireless Attacks 16.2.1 Reconnaissance Attack 16.2.2 Access Attacks 16.2.3 Man-in-the-Middle Attack 16.2.4 Denial of Services (DOS) 16.3 Securing Wireless Transmissions 16.3.1 Protecting the Confidentiality 16.3.2 Protecting the Modification 16.3.3 Preventing Interruption of Denial-of-Service Attack 16.4 Proposed Model for Securing the Client Over the Channel 16.5 Conclusion References

Read more less

Book SynopsisBackscattering and RF Sensing for Future Wireless Communication Discover what lies ahead in wireless communication networks with this insightful and forward-thinking book written by experts in the fieldBackscattering and RF Sensing for Future Wireless Communication delivers a concise and insightful picture of emerging and future trends in increasing the efficiency and performance of wireless communication networks. The book shows how the immense challenge of frequency saturation could be met via the deployment of intelligent planar electromagnetic structures. It provides an in-depth coverage of the fundamental physics behind these structures and assesses the enhancement of the performance of a communication network in challenging environments, like densely populated urban centers. The distinguished editors have included resources from a variety of leading voices in the field who discuss topics such as the engineering of metasurfaces at a large scale, the electromagnetic analysis of pTable of Contents 1. Intelligent Reflective Surfaces – State of the art Jalil ur Rehman Kazim, Hasan T. Abbas, Muhammad A. Imran, Qammer H. Abbasi 2. Signal Modulation Schemes in Backscatter Communications Yuan Ding, George Goussetis, Ricardo Correia, Nuno Borges Carvalho, Romwald Lihakanga, and Chaoyun Song 3. Electromagnetic Waves Scattering Characteristics of Metasurfaces Muhammad Ali Babar Abbasi, Dmitry E. Zelenchuk, Abdul Quddious 4. Metasurfaces Based on Huygen’s Wave Front Manipulation: A review Abubakar Sharif, Jun Ouyang, Ayman Abdulhadi Althuwayb, Kamran Arshad, Muhammad A. Imran, Qammer H. Abbasi 5. Metasurface: An Insight into Its Applications Fahad Ahmed and Nosherwan Shoaib 6. The Role of Smart Metasurfaces in Smart Grid Energy Management I. Safak Bayram, Muhammad Ismail, and Raka Jovanovic 7. Passive UHF RFID Tag Antennas Based Sensing for Internet of Things Paradigm Abubakar Sharif, Jun Ouyang, Kamran Arshad, Muhammad A. Imran, Qammer H. Abbasi 8. RF Sensing for Healthcare Applications Syed Aziz Shah, Hasan Abbas, Muhammad A. Imran and Qammer H. Abbasi 9. Electromagnetic Wave Manipulation with Metamaterials and Metasurfaces for Future Communication Technologies Muhammad Qasim Mehmood, Junsuk Rho, and Muhammad Zubair 10. Conclusion Qammer H. Abbasi, Hasan T. Abbas, Akram Alomainy, and Muhammad A. Imran

Read more less

Book SynopsisTable of ContentsPreface xv List of Contributors xix Acronyms List xx 1 Hands-on Wireless Communication Experience 1Hüseyin Arslan 1.1 Importance of Laboratory-Based Learning of Wireless Communications 1 1.2 Model for a Practical Lab Bench 3 1.3 Examples of Co-simulation with Hardware 6 1.4 A Sample Model for a Laboratory Course 8 1.4.1 Introduction to the SDR and Testbed Platform 11 1.4.2 Basic Simulation 11 1.4.3 Measurements and Multidimensional Signal Analysis 11 1.4.4 Digital Modulation 12 1.4.5 Pulse Shaping 13 1.4.6 RF Front-end and RF Impairments 13 1.4.7 Wireless Channel and Interference 14 1.4.8 Synchronization and Channel Estimation 15 1.4.9 OFDM Signal Analysis and Performance Evaluation 15 1.4.10 Multiple Accessing 16 1.4.11 Independent Project Development Phase 16 1.4.11.1 Software Defined Radio 17 1.4.11.2 Dynamic Spectrum Access and CR Experiment 17 1.4.11.3 Wireless Channel 17 1.4.11.4 Wireless Channel Counteractions 18 1.4.11.5 Antenna Project 18 1.4.11.6 Signal Intelligence 18 1.4.11.7 Channel, User, and Context Awareness Project 19 1.4.11.8 Combination of DSP Lab with RF and Microwave Lab 19 1.4.11.9 Multiple Access and Interference Management 19 1.4.11.10 Standards 20 1.5 Conclusions 20 References 20 2 Performance Metrics and Measurements 23Hüseyin Arslan 2.1 Signal Quality Measurements 23 2.1.1 Measurements Before Demodulation 24 2.1.2 Measurements During and After Demodulation 25 2.1.2.1 Noise Figure 26 2.1.2.2 Channel Frequency Response Estimation 26 2.1.3 Measurements After Channel Decoding 26 2.1.3.1 Relation of SNR with BER 27 2.1.4 Error Vector Magnitude 27 2.1.4.1 Error-Vector-Time and Error-Vector-Frequency 29 2.1.4.2 Relation of EVM with Other Metrics 30 2.1.4.3 Rho 31 2.1.5 Measures After Speech or Video Decoding 31 2.2 Visual Inspections and Useful Plots 32 2.2.1 Advanced Scatter Plot 39 2.3 Cognitive Radio and SDR Measurements 40 2.4 Other Measurements 42 2.5 Clarifying dB and dBm 44 2.6 Conclusions 45 References 45 3 Multidimensional Signal Analysis 49Hüseyin Arslan 3.1 Why Multiple Dimensions in a Radio Signal? 49 3.2 Time Domain Analysis 52 3.2.1 CCDF and PAPR 53 3.2.2 Time Selectivity Measure 56 3.3 Frequency Domain Analysis 57 3.3.1 Adjacent Channel Power Ratio 59 3.3.2 Frequency Selectivity Measure 61 3.4 Joint Time-Frequency Analysis 62 3.5 Code Domain Analysis 64 3.5.1 Code Selectivity 66 3.6 Correlation Analysis 67 3.7 Modulation Domain Analysis 68 3.8 Angular Domain Analysis 68 3.8.1 Direction Finding 68 3.8.2 Angular Spread 70 3.9 MIMO Measurements 71 3.9.1 Antenna Correlation 72 3.9.2 RF Cross-Coupling 72 3.9.3 EVM Versus Antenna Branches 73 3.9.4 Channel Parameters 73 3.10 Conclusions 73 References 74 4 Simulating a Communication System 77Muhammad Sohaib J. Solaija and Hüseyin Arslan 4.1 Simulation: What,Why? 77 4.2 Approaching a Simulation 78 4.2.1 Strategy 78 4.2.2 General Methodology 80 4.3 Basic Modeling Concepts 81 4.3.1 System Modeling 81 4.3.2 Subsystem Modeling 81 4.3.3 Stochastic Modeling 82 4.4 What is a Link/Link-level Simulation? 82 4.4.1 Source and Source Coding 82 4.4.2 Channel Coding 83 4.4.3 Symbol Mapping/Modulation 83 4.4.4 Upsampling 84 4.4.5 Digital Filtering 84 4.4.6 RF Front-end 85 4.4.7 Channel 86 4.4.8 Synchronization and Equalization 87 4.4.9 Performance Evaluation and Signal Analysis 87 4.5 Communication in AWGN – A Simple Case Study 88 4.5.1 Receiver Design 88 4.6 Multi-link vs. Network-level Simulations 88 4.6.1 Network Layout Generation 90 4.6.1.1 Hexagonal Grid 90 4.6.1.2 PPP-based Network Layout 91 4.7 Practical Issues 93 4.7.1 Monte Carlo Simulations 93 4.7.2 Random Number Generation 94 4.7.2.1 White Noise Generation 94 4.7.2.2 Random Binary Sequence 94 4.7.3 Values of Simulation Parameters 95 4.7.4 Confidence Interval 95 4.7.5 Convergence/Stopping Criterion 95 4.8 Issues/Limitations of Simulations 95 4.8.1 Modeling Errors 96 4.8.1.1 Errors in System Model 96 4.8.1.2 Errors in Subsystem Model 96 4.8.1.3 Errors in Random Process Modeling 96 4.8.2 Processing Errors 96 4.9 Conclusions 97 References 97 5 RF Impairments 99Hüseyin Arslan 5.1 Radio Impairment Sources 99 5.2 IQ Modulation Impairments 102 5.3 PA Nonlinearities 106 5.4 Phase Noise and Time Jitter 110 5.5 Frequency Offset 112 5.6 ADC/DAC Impairments 113 5.7 Thermal Noise 114 5.8 RF Impairments and Interference 114 5.8.1 Harmonics and Intermodulation Products 114 5.8.2 Multiple Access Interference 116 5.9 Conclusions 118 References 118 6 Digital Modulation and Pulse Shaping 121Hüseyin Arslan 6.1 Digital Modulation Basics 121 6.2 Popularly Used Digital Modulation Schemes 123 6.2.1 PSK 123 6.2.2 FSK 125 6.2.2.1 GMSK and Approximate Representation of GSM GMSK Signal 127 6.2.3 QAM 129 6.2.4 Differential Modulation 132 6.3 Adaptive Modulation 133 6.3.1 Gray Mapping 135 6.3.2 Calculation of Error 135 6.3.3 Relation of Eb No with SNR at the receiver 138 6.4 Pulse-Shaping Filtering 138 6.5 Conclusions 146 References 146 7 OFDM Signal Analysis and Performance Evaluation 147Hüseyin Arslan 7.1 Why OFDM? 147 7.2 Generic OFDM System Design and Its Evaluation 149 7.2.1 Basic CP-OFDM Transceiver Design 150 7.2.2 Spectrum of the OFDM Signal 151 7.2.3 PAPR of the OFDM Signal 155 7.2.4 Performance in Multipath Channel 157 7.2.4.1 Time-Dispersive Multipath Channel 157 7.2.4.2 Frequency-Dispersive Multipath Channel 161 7.2.5 Performance with Impairments 162 7.2.5.1 Frequency Offset 163 7.2.5.2 Symbol Timing Error 167 7.2.5.3 Sampling Clock Offset 170 7.2.5.4 Phase Noise 171 7.2.5.5 PA Nonlinearities 172 7.2.5.6 I/Q Impairments 175 7.2.6 Summary of the OFDM Design Considerations 177 7.2.7 Coherent versus Differential OFDM 178 7.3 OFDM-like Signaling 180 7.3.1 OFDM Versus SC-FDE 180 7.3.2 Multi-user OFDM and OFDMA 181 7.3.3 SC-FDMA and DFT-S-OFDM 182 7.4 Case Study: Measurement-Based OFDM Receiver 185 7.4.1 System Model 185 7.4.1.1 Frame Format 186 7.4.1.2 OFDM Symbol Format 186 7.4.1.3 Baseband Transmitter Blocks and Transmitted Signal Model 186 7.4.1.4 Received Signal Model 188 7.4.2 Receiver Structure and Algorithms 189 7.4.2.1 Packet Detection 191 7.4.2.2 Frequency Offset Estimation and Compensation 191 7.4.2.3 Symbol Timing Estimation 192 7.4.2.4 Packet-end Detection and Packet Extraction 193 7.4.2.5 Channel Estimation and Equalization 194 7.4.2.6 Pilot Tracking 195 7.4.2.7 Auto-modulation Detection 195 7.4.3 FCH Decoding 196 7.4.4 Test and Measurements 196 7.5 Conclusions 197 References 198 8 Analysis of Single-Carrier Communication Systems 201Hüseyin Arslan 8.1 A Simple System in AWGN Channel 201 8.2 Flat Fading (Non-Dispersive) Multipath Channel 210 8.3 Frequency-Selective (Dispersive) Multipath Channel 215 8.3.1 Time-Domain Equalization 219 8.3.2 Channel Estimation 223 8.3.3 Frequency-Domain Equalization 226 8.4 Extension of Dispersive Multipath Channel to DS-CDMA-based Wideband Systems 229 8.5 Conclusions 232 References 232 9 Multiple Accessing, Multi-Numerology, Hybrid Waveforms 235Mehmet Mert ¸Sahin and Hüseyin Arslan 9.1 Preliminaries 235 9.1.1 Duplexing 236 9.1.2 Downlink Communication 237 9.1.3 Uplink Communication 238 9.1.4 Traffic Theory and Trunking Gain 238 9.2 Orthogonal Design 241 9.2.1 TDMA 241 9.2.2 FDMA 242 9.2.3 Code Division Multiple Access (CDMA) 243 9.2.4 Frequency Hopped Multiple Access (FHMA) 245 9.2.5 Space Division Multiple Access (SDMA) 246 9.2.5.1 Multiuser Multiple-input Multiple-output (MIMO) 247 9.3 Non-orthogonal Design 249 9.3.1 Power-domain Non-orthogonal Multiple Access (PD-NOMA) 250 9.3.2 Code-domain Non-orthogonal Multiple Access 251 9.4 Random Access 253 9.4.1 ALOHA 253 9.4.2 Carrier Sense Multiple Accessing (CSMA) 254 9.4.3 Multiple Access Collision Avoidance (MACA) 254 9.4.4 Random Access Channel (RACH) 255 9.4.5 Grant-free Random Access 255 9.5 Multiple Accessing with Application-Based Hybrid Waveform Design 256 9.5.1 Multi-numerology Orthogonal Frequency Division Multiple Access (OFDMA) 256 9.5.2 Radar-Sensing and Communication (RSC) Coexistence 258 9.5.3 Coexistence of Different Waveforms in Multidimensional Hyperspace for 6G and Beyond Networks 260 9.6 Case Study 261 Appendix: Erlang B table 263 References 263 10 Wireless Channel and Interference 267Abuu B. Kihero, Armed Tusha, and Hüseyin Arslan 10.1 Fundamental Propagation Phenomena 267 10.2 Multipath Propagation 269 10.2.1 Large-Scale Fading 269 10.2.1.1 Path Loss 270 10.2.1.2 Shadowing 271 10.2.2 Small-Scale Fading 272 10.2.2.1 Characterization of Time-Varying Channels 273 10.2.2.2 Rayleigh and Rician Fading Distributions 274 10.2.3 Time, Frequency and Angular Domains Characteristics of Multipath Channel 276 10.2.3.1 Delay Spread 276 10.2.3.2 Angular Spread 279 10.2.3.3 Doppler Spread 281 10.2.4 Novel Channel Characteristics in the 5G Technology 284 10.3 Channel as a Source of Interference 288 10.3.1 Interference due to Large-Scale Fading 288 10.3.1.1 Cellular Systems and CoChannel Interference 288 10.3.1.2 Cochannel Interference Control via Resource Assignment 289 10.3.2 Interference due to Small-Scale Fading 292 10.4 Channel Modeling 293 10.4.1 Analytical Channel Models 294 10.4.1.1 Correlation-based Models 294 10.4.1.2 Propagation-Motivated Models 294 10.4.2 Physical Models 295 10.4.2.1 Deterministic Model 295 10.4.2.2 Geometry-based Stochastic Model 295 10.4.2.3 Nongeometry-based Stochastic Models 296 10.4.3 3GPP 5G Channel Models 297 10.4.3.1 Tapped Delay Line (TDL) Model 297 10.4.3.2 Clustered Delay Line (CDL) Model 298 10.4.3.3 Generating Channel Coefficients Using CDL Model 299 10.4.4 Role of Artificial Intelligence (AI) in Channel Modeling 300 10.5 Channel Measurement 301 10.5.1 Frequency Domain Channel Sounder 303 10.5.1.1 Swept Frequency/Chirp Sounder 303 10.5.2 Time Domain Channel Sounder 304 10.5.2.1 Periodic Pulse/Impulse Sounder 304 10.5.2.2 Correlative/Pulse Compression Sounders 305 10.5.3 Challenges of Practical Channel Measurement 308 10.6 Channel Emulation 308 10.6.1 Baseband and RF Domain Channel Emulators 309 10.6.2 Reverberation Chambers as Channel Emulator 309 10.6.2.1 General Principles 309 10.6.2.2 Emulating Multipath Effects Using RVC 311 10.6.3 Commercial Wireless Channel Emulators 318 10.7 Wireless Channel Control 319 10.8 Conclusion 321 References 321 11 Carrier and Time Synchronization 325Musab Alayasra and Hüseyin Arslan 11.1 Signal Modeling 325 11.2 Synchronization Approaches 327 11.3 Carrier Synchronization 329 11.3.1 Coarse Frequency Offset Compensation 331 11.3.1.1 DFT-based Coarse Frequency Offset Compensation 331 11.3.1.2 Phase-based Coarse Frequency Offset Compensation 333 11.3.2 Fine Frequency Offset Compensation 335 11.3.2.1 Feedforward MLE-Based Frequency Offset Compensation 335 11.3.2.2 Feedback Heuristic-Based Frequency Offset Compensation 340 11.3.3 Carrier Phase Offset Compensation 344 11.4 Time Synchronization 345 11.4.1 Frame Synchronization 346 11.4.2 Symbol Timing Synchronization 347 11.4.2.1 Feedforward MLE-based Symbol Timing Synchronization 348 11.4.2.2 Feedback Heuristic-based Symbol Timing Synchronization 349 11.5 Conclusion 352 References 353 12 Blind Signal Analysis 355Mehmet Ali Aygül, Ahmed Naeem, and Hüseyin Arslan 12.1 What is Blind Signal Analysis? 355 12.2 Applications of Blind Signal Analysis 355 12.2.1 Spectrum Sensing 356 12.2.2 Parameter Estimation and Signal Identification 357 12.2.2.1 Parameter Estimation 357 12.2.2.2 Signal Identification 357 12.2.3 Radio Environment Map 358 12.2.4 Equalization 360 12.2.5 Modulation Identification 361 12.2.6 Multi-carrier (OFDM) Parameters Estimation 362 12.3 Case Study: Blind Receiver 363 12.3.1 Bandwidth Estimation 364 12.3.2 Carrier Frequency Estimation 365 12.3.3 Symbol Rate Estimation 366 12.3.4 Pulse-Shaping and Roll-off Factor Estimation 366 12.3.5 Optimum Sampling Phase Estimation 368 12.3.6 Timing Recovery 369 12.3.7 Frequency Offset and Phase Offset Estimation 371 12.4 Machine Learning for Blind Signal Analysis 372 12.4.1 Deep Learning 374 12.4.2 Applications of Machine Learning 375 12.4.2.1 Signal and Interference Identification 375 12.4.2.2 Multi-RF Impairments Identification, Separation, and Classification 375 12.4.2.3 Channel Modeling and Estimation 376 12.4.2.4 Spectrum Occupancy Prediction 377 12.5 Challenges and Potential Study Items 378 12.5.1 Challenges 378 12.5.2 Potential Study Items 379 12.6 Conclusions 379 References 380 13 Radio Environment Monitoring 383Halise Türkmen, Saira Rafique, and Hüseyin Arslan 13.1 Radio Environment Map 384 13.2 Generalized Radio Environment Monitoring 385 13.2.1 Radio Environment Monitoring with the G-REM Framework 387 13.3 Node Types 388 13.4 Sensing Modes 388 13.5 Observable Data, Derivable Information and Other Sources 389 13.6 Sensing Methods 389 13.6.1 Sensing Configurations 390 13.6.2 Processing Data and Control Signal 391 13.6.2.1 Channel State Information (CSI) 391 13.6.2.2 Channel Impulse Response (CIR) 393 13.6.2.3 Channel Frequency Response (CFR) 393 13.6.3 Blind Signal Analysis 393 13.6.4 Radio Detection and Ranging 394 13.6.4.1 Radar Test-bed 401 13.6.5 Joint Radar and Communication 402 13.6.5.1 Coexistence 403 13.6.5.2 Co-Design 403 13.6.5.3 RadComm 405 13.6.5.4 CommRad 406 13.7 Mapping Methods 407 13.7.1 Signal Processing Algorithms 407 13.7.2 Interpolation Techniques 408 13.7.2.1 Inverse Distance Weighted Interpolation 408 13.7.2.2 Kriging’s Interpolation 409 13.7.3 Model-Based Techniques 410 13.7.4 Learning-Based Techniques 410 13.7.5 Hybrid Techniques 410 13.7.6 Case Study: Radio Frequency Map Construction 410 13.7.6.1 Radio Frequency Map Construction Test-bed for CR 411 13.7.7 Case Study: Wireless Local Area Network/Wi-Fi Sensing 413 13.7.7.1 WLAN Sensing Test-bed for Gesture Detection 415 13.8 Applications of G-REM 416 13.8.1 Cognitive Radios 417 13.8.2 Security 417 13.8.2.1 PHY Layer Security 417 13.8.2.2 Cross-Layer Security 417 13.8.3 Multi-Antenna Communication Systems 418 13.8.3.1 UE and Obstacle Tracking for Beam Management 418 13.8.3.2 No-Feedback Channel Estimation for FDD MIMO and mMIMO Systems 418 13.8.4 Formation and Management of Ad Hoc Networks and Device-to-Device Communication 418 13.8.5 Content Caching 419 13.8.6 Enabling Flexible Radios for 6G and Beyond Networks 419 13.8.7 Non-Communication Applications 419 13.9 Challenges and Future Directions 420 13.9.1 Security 420 13.9.2 Scheduling 421 13.9.3 Integration of (New) Technologies 421 13.9.3.1 Re-configurable Intelligent Surfaces 421 13.9.3.2 Quantum Radar 421 13.10 Conclusion 422 References 422 Index 425

Read more less

Book SynopsisMassive Connectivity Learn to support more devices and sensors in Internet of Things applications through NOMA and machine-type communication Non-orthogonal multiple access (NOMA) has held much interest due to its ability to provide a higher spectral efficiencysuch as more bits per unit bandwidth in Hertzthan other, orthogonal multiple access schemes. The majority of this research focuses on the application of NOMA to downlink channels (from base station to users) in cellular systems as its use for uplink (users to base station) is somewhat circumscribed. However, NOMA has recently been employed in contention-based uplink access, which has shown an improvement in performance that allows an increase in the number of users that can be supported. As a result, NOMA is promising for machine-type communication (MTC) in 5G systems and beyond, making it a key enabler of the Internet of Things (IoT). Massive Connectivity provides an in-depth, comprehensive view of Table of ContentsPreface xiii 1 Introduction 1 1.1 Machine-Type Communication 1 1.2 Non-Orthogonal Multiple Access 3 1.3 NOMA for MTC 4 1.4 An Overview of Probability and Random Processes 6 1.4.1 Review of Probability 6 1.4.2 Random Variables 7 1.4.3 Random Processes 14 1.4.4 Markov Chains 15 2 Single-User and Multiuser Systems 19 2.1 A Single-User System 19 2.1.1 Signal Representation 20 2.1.2 Transmission of Signal Sequences 21 2.1.3 ML Decoding 23 2.1.4 ML Decoding over Fading Channels 26 2.1.5 Achievable Rate 28 2.2 Multiuser Systems 33 2.2.1 Broadcast Channels 34 2.2.2 Multiple Access Channels 37 2.3 Further Reading 41 3 OMA and NOMA 43 3.1 Orthogonal Multiple Access 43 3.1.1 Time Division Multiple Access 43 3.1.2 Frequency Division Multiple Access 46 3.1.3 Orthogonal Frequency Division Multiple Access 47 3.2 Non-Orthogonal Multiple Access 51 3.2.1 Downlink NOMA 52 3.2.2 Uplink NOMA 57 3.3 Power and Rate Allocation 60 3.3.1 System with Known Instantaneous CSI 60 3.3.2 System with Unknown Instantaneous CSI 67 3.4 Code Division Multiple Access 73 3.4.1 DS-CDMA 74 3.4.2 Multiuser Detection Approaches 78 3.5 Further Reading 84 4 Random Access Systems 87 4.1 ALOHA Systems 88 4.1.1 Single Channel Random Access 88 4.1.2 Multi-Channel S-ALOHA 90 4.2 Throughput Analysis 91 4.2.1 Pure ALOHA 91 4.2.2 Slotted ALOHA 92 4.2.3 Multichannel ALOHA 94 4.3 Analysis with a Finite Number of Users 98 4.3.1 A Markov Chain 98 4.3.2 Drift Analysis 100 4.4 Analysis with an In_nite Number of Users 102 4.4.1 Constant Re-transmission Probability 102 4.4.2 Adaptive Re-transmission Probability 104 4.5 Fast Retrial 107 4.6 Multiuser Detection 108 4.6.1 Compressive Random Access 108 4.6.2 Throughput Analysis 110 4.7 Further Reading 114 5 NOMA-based Random Access 117 5.1 NOMA to Random Access 117 5.1.1 S-ALOHA with NOMA 118 5.1.2 More Power Levels 122 5.2 Multichannel ALOHA with NOMA 127 5.2.1 Multichannel ALOHA with NOMA and Throughput Analysis 128 5.2.2 Channel-Dependent Selection 132 5.3 Opportunistic NOMA 137 5.3.1 System Model 137 5.3.2 Throughput Analysis 140 5.3.3 Opportunistic NOMA for Channel Selection 147 5.4 NOMA-based Random Access with Multiuser Detection 152 5.4.1 Compressive Random Access 152 5.4.2 Layered CRA 154 5.4.3 Performance under Realistic Conditions 159 5.5 Further Reading 161 6 Application of NOMA to MTC in 5G 163 6.1 Machine-Type Communication 163 6.1.1 IoT Connectivity 163 6.1.2 Random Access Schemes for MTC 164 6.2 A Model with Massive MIMO 168 6.2.1 Massive MIMO 168 6.2.2 Two-step Random Access with Massive MIMO 173 6.2.3 Throughput Analysis 174 6.3 NOMA for High-Throughput MTC 177 6.3.1 Co-existing Preambles and Data Packets 178 6.3.2 Maximum Throughput Comparison 180 6.3.3 Limitations 184 6.4 Layered Preambles for Heterogeneous Devices 185 6.4.1 Heterogeneous Devices in MTC 185 6.4.2 Design of Layered Preambles 187 6.4.3 Performance Analysis 189 6.5 Further Reading 195 7 Game-Theoretic Perspective of NOMA-based Random Access 197 7.1 Background of Game Theory 197 7.1.1 Normal-Form Games 198 7.1.2 Nash Equilibrium 200 7.1.3 Mixed Strategies 200 7.2 Random Access Game 202 7.2.1 Normal-Form and NE 203 7.2.2 Mixed Strategies 204 7.3 NOMA-ALOHA Game 204 7.3.1 Single-Channel NOMA-ALOHA Game 205 7.3.2 Multichannel NOMA-ALOHA Game 216 7.4 Fictitious Play 221 7.4.1 A Model for Fictitious Play 221 7.4.2 Convergence 223 7.5 Evolutionary Game Theory and Its Application 227 7.5.1 Population Games 227 7.5.2 Replicator Dynamics and Evolutionary Stable State 228 7.5.3 Stability of the Replicator Dynamics 231 7.5.4 Application to NOMA 232 7.6 Further Reading 234 Index 247

Read more less

Book SynopsisProvides a thorough introduction to the development, operation, maintenance, and troubleshooting of mobile communications systems Mobile Communications Systems Development: A Practical Introduction for System Understanding, Implementation, and Deployment is a comprehensive how to manual for mobile communications system design, deployment, and support. Providing a detailed overview of end-to-end system development, the book encompasses operation, maintenance, and troubleshooting of currently available mobile communication technologies and systems. Readers are introduced to different network architectures, standardization, protocols, and functions including 2G, 3G, 4G, and 5G networks, and the 3GPP standard. In-depth chapters cover the entire protocol stack from the Physical (PHY) to the Application layer, discuss theoretical and practical considerations, and describe software implementation based on the 3GPP standardized technical specifications. The book includes figures, tables, and sample computer code to help readers thoroughly comprehend the functions and underlying concepts of a mobile communications network. Each chapter includes an introduction to the topic and a chapter summary. A full list of references, and a set of exercises are also provided at the end of the book to test comprehension and strengthen understanding of the material. Written by a respected professional with more than 20 years' experience in the field, this highly practical guide: Provides detailed introductory information on GSM, GPRS, UMTS, and LTE mobile communications systems and networksDescribes the various aspects and areas of the LTE system air interface and its protocol layersCovers troubleshooting and resolution of mobile communications systems and networks issuesDiscusses the software and hardware platforms used for the development of mobile communications systems network elementsIncludes 5G use cases, enablers, and architectures that cover the 5G NR (New Radio) and 5G Core Network Mobile Communications Systems Development is perfect for graduate and postdoctoral students studying mobile communications and telecom design, electronic engineering undergraduate students in their final year, research and development engineers, and network operation and maintenance personnel.Trade Review"The author provides a comprehensive summary on the mobile communications systems covering 2G, 3G, 4G and 5G. The great addition to the theoretical foundations are practical elements including system operation and development aspects, with multitude practical examples and self-assessment. This handbook shall be useful for telecom practitioners including radio and core network engineers. It’s also a good source for software engineers from a different domain who would like to enter the telco domain. It shall be of interest to those, especially in present times where IT, software development and mobile communications are closer to each other than ever before."- Marcin Dryjański, Ph.D., PRINCIPAL CONSULTANT / CEOTable of ContentsAbout the Author xiv Preface xv Acknowledgments xviii List of Abbreviations xix 1 Introduction 1 Part I Network Architectures, Standardization, Protocols, and Functions 3 2 Network Architectures, Standardizations Process 5 2.1 Network Elements and Basic Networks Architectures 5 2.1.1 GSM (2G) Network Architecture 6 2.1.2 General Packet Radio Service (GPRS-2.5G) Network Architecture 7 2.1.3 Universal Mobile Telecommunications System (3G) Network Architecture 7 2.1.4 LTE (4G) Network Architecture 8 2.1.5 GSM, UMTS, LTE, and 5G Network Elements: A Comparison 9 2.1.6 Circuit Switched (CS) vs Packet Switched (PS) 9 2.2 Mobile Communication Network Domains 10 2.2.1 AN Domain 10 2.2.2 Core Network (CN) Domain 11 2.2.3 Network Domains and Its Elements 11 2.2.4 Example: End-to-End Mobile Network Information Flow 12 2.2.5 Example: GSM MO Call 13 2.3 Mobile Communications Systems Evolutions 14 2.3.1 Evolutions of Air Interface 14 2.3.2 Evolutions of 3GPP Networks Architectures 16 2.4 Mobile Communications Network System Engineering 19 2.4.1 Mobility Management 19 2.4.2 Air Interface Management 20 2.4.3 Subscribers and Services Management 20 2.4.4 Security Management 20 2.4.5 Network Maintenance 20 2.5 Standardizations of Mobile Communications Networks 21 2.5.1 3rd Generation Partnership Project (3GPP) 21 2.5.2 3GPP Working Groups 21 2.5.3 3GPP Technical Specification and Technical Report 22 2.5.4 Stages of a 3GPP Technical Specification 22 2.5.5 Release Number of 3GPP Technical Specification 22 2.5.6 3GPP Technical Specification Numbering Nomenclature 23 2.5.7 Vocabulary of 3GPP Specifications 24 2.5.8 Examples in a 3GPP Technical Specification 24 2.5.9 Standardization of Technical Specifications by 3GPP 24 2.5.10 Scope of 3GPP Technical Specification (TS) 24 2.5.11 3GPP TS for General Description of a Protocol Layer 25 2.5.12 3GPP TS Drafting Rules: Deriving Requirements 25 2.5.13 Download 3GPP Technical Specifications 25 2.5.14 3GPP Change Requests 26 2.5.15 Learnings from 3GPP Meetings TDocs 26 2.6 3GPP Releases and Its Features 26 Chapter Summary 27 3 Protocols, Interfaces, and Architectures 29 3.1 Protocol Interface and Its Stack 29 3.1.1 Physical Interface 30 3.1.2 Logical Interface 30 3.1.3 Logical Interfaces’ Names and Their Protocol Stack 33 3.1.4 Examples of Logical Interface and Its Protocol Layers 35 3.2 Classifications of Protocol Layers 36 3.2.1 Control Plane or Signaling Protocols 36 3.2.2 User Plane Protocols 38 3.3 Grouping of UMTS, LTE, and 5G Air Interface Protocol Layers 39 3.3.1 Access Stratum (AS): UMTS UE – UTRAN; LTE UE – E-UTRAN;5G UE - NG-RAN 39 3.3.2 Non-Access Stratum: UMTS UE – CN, LTE UE – EPC; 5G UE-Core 41 3.4 Initialization of a Logical Interface 42 3.5 Protocol Layer Termination 43 3.6 Protocol Sublayers 43 3.7 Protocol Conversion 44 3.8 Working Model of a 3GPP Protocol Layer: Services and Functions 45 3.9 General Protocol Model Between RAN and CN (UMTS, LTE, 5G) 46 3.10 Multiple Transport Networks, Protocols, and Physical Layer Interfaces 47 3.11 How to Identify and Understand Protocol Architectures 49 3.11.1 Identifying a Logical Interface, Protocol Stack, and Its Layers 49 3.11.2 Identification of Technical Requirements Using Interface Name 51 3.12 Protocol Layer Procedures over CN Interfaces 51 3.12.1 Similar Functions and Procedures over the CN Interfaces 52 3.12.2 Specific Functions and Procedures over the CN Interfaces 53 Chapter Summary 54 4 Encoding and Decoding of Messages 55 4.1 Description and Encoding/Decoding of Air Interface Messages 55 4.1.1 Encoding/Decoding: Air Interface Layer 3 Messages 56 4.1.2 Encoding/Decoding: LTE and 5G NR Layer 2: RLC Protocol 60 4.1.3 Encoding/Decoding: LTE and 5G NR Layer 2: MAC Protocol 60 4.1.4 CSN.1 Encoding/Decoding: GPRS Layer 2 Protocol (RLC/MAC) 60 4.1.5 ASN.1 Encoding/Decoding: UMTS, LTE, and 5G NR Layer 3 Protocol 61 4.1.6 Direct/Indirect Encoding Method 62 4.1.7 Segmented Messages over the Air Interface 63 4.1.8 Piggybacking a Signaling Message 63 4.2 Encoding/Decoding of Signaling Messages: RAN and CN 64 Chapter Summary 65 5 Network Elements: Identities and Its Addressing 67 5.1 Network Elements and Their Identities 67 5.2 Permanent Identities 68 5.3 Temporary Identities Assigned by CN 69 5.3.1 GSM System Temporary Identities 69 5.3.2 GPRS System Temporary Identities 69 5.3.3 LTE/EPS System Temporary Identities 70 5.4 Temporary Identities Assigned by RAN: RNTI 72 5.5 Usages of Network Identities 73 5.6 Native and Mapped Network Identities 73 5.7 LTE UE Application Protocol Identity 75 Chapter Summary 76 6 Interworking and Interoperations of Mobile Communications Networks 77 6.1 Requirements and Types of Interworking 77 6.2 Interworking Through Enhanced Network Elements 78 6.2.1 Interworking for Voice Call Through IMS: VoLTE 79 6.2.1.1 IP Multimedia Subsystem (IMS) 80 6.2.1.2 UE Registration and Authentication 81 6.2.2 Interworking for VoLTE Call Through LTE/EPS: SRVCC 83 6.2.3 Interworking for Voice Call Through LTE/EPS: CSFB 85 6.3 Interworking Through Legacy Network Elements 88 6.4 Interworking Between LTE/EPS and 5G Systems 89 6.5 Interoperations of Networks: LTE/EPS Roaming 90 6.5.1 Roaming Through Interoperations of Enhanced Networks Elements 90 6.5.2 Roaming Through Interoperations of Legacy Networks Elements 92 6.6 UE Mode of Operation 92 6.7 Function of E-UTRAN in a VoLTE Call 95 Chapter Summary 95 7 Load Balancing and Network Sharing 97 7.1 Core Network Elements Load Balancing 97 7.1.1 Identification of NAS Node: NRI and Its Source 99 7.1.2 NAS Node Selection Function 99 7.2 Network Sharing 102 7.2.1 GSM/GPRS/LTE RAN Sharing Through MOCN Feature 103 7.2.2 5G NG‐RAN Sharing Through MOCN Feature (Release 16) 109 Chapter Summary 110 8 Packets Encapsulations and Their Routing 111 8.1 User Data Packets Encapsulations 111 8.1.1 Packets Encapsulations at the CN and RAN 112 8.1.1.1 GPRS Tunneling Protocol ( GTP) 112 8.1.1.2 GTP Functions 112 8.1.1.3 GTP User Plane PDU: G-PDU 113 8.1.1.4 GTP Control Plane PDU 114 8.1.1.5 Example: GTP and Packet Encapsulations at LTE EPC 115 8.1.2 Packet Encapsulations over Air Interface 115 8.2 IP Packet Routing in Mobile Communications Networks 116 8.3 IP Header Compression and Decompression 117 Chapter Summary 119 9 Security Features in Mobile Communications Networks 121 9.1 A Brief on the Security Architecture: Features and Mechanisms 121 9.2 Security Features and Its Mechanisms 123 9.3 GSM Security Procedures 126 9.4 UMTS, LTE, and 5G: AS and NAS Layer Security Procedures 127 9.5 Security Contexts 130 9.6 Security Interworking 130 Chapter Summary 132 Part II Operations and Maintenances 133 10 Alarms and Faults Managements 135 10.1 Network Elements Alarm and Its Classifications 135 10.2 Sources of Abnormal Events and Alarms 136 10.3 Identifying Sources of Alarms from 3GPP TSs 136 10.3.1 Abnormal Conditions 136 10.3.2 Protocol Layer Error Handling 137 10.3.3 Abnormal Conditions Due to Local Errors 138 10.4 Design and Implementation of an Alarm Management System 138 10.4.1 Design and Components of an Alarm 139 10.4.2 Alarm Application Programming Interfaces (APIs) 139 10.4.3 Alarm Database 139 10.5 Alarm Due to Protocol Error 140 10.5.1 Sample Protocol Error Alarm Description 142 10.6 Alarm Due to Abnormal Conditions 142 10.6.1 Normal Scenario 143 10.6.2 Abnormal Scenario 143 10.6.3 Sample Alarm Description 144 10.6.4 Sample Alarm Generation 145 10.6.5 Sample Protocol Error Alarm Generation 145 10.7 How to Troubleshoot Protocol Error Using the Alarm Data 146 Chapter Summary 146 11 Performance Measurements and Optimizations of Mobile Communications Networks 147 11.1 Counters for Performance Measurements and Optimizations 147 11.2 Performance and Optimizations Management System 149 11.3 Key Performance Indicator (KPI) 150 11.3.1 What Is a KPI? 150 11.3.2 KPI Domains 150 11.3.3 KPI for Signaling or Control Plane 152 11.3.4 KPI for User or Data Plane 153 11.3.5 KPI Categories 154 11.3.6 KPI Evaluation Steps 155 11.3.7 Troubleshooting and Improving KPI 156 11.3.8 Components of a KPI Definition 157 Chapter Summary 157 12 Troubleshooting of Mobile Communications Networks Issues 159 12.1 Air Interface-Related Issues 159 12.1.1 Drive Test, Data Collection, and Its Analysis 160 12.2 Debugging Issues with IP-Based Logical Interface 160 12.2.1 IP Protocol Analyzer 161 12.2.2 Network/Application Throughput Issue 161 12.2.3 Switch Port Mirroring 161 12.3 Conformance Testing Issues 162 12.3.1 Example: Mobile Device (MS)/User Equipment (UE) Conformance Test 163 12.3.2 Example: Location Area Update Request 163 12.4 Interoperability Testing (IOT) Issues 164 12.5 Interworking Issues 165 12.6 Importance of Log/Traces and Its Collections 166 12.7 Steps for Troubleshooting 167 Chapter Summary 170 Part III Mobile Communications Systems Development 171 13 Core Software Development Fundamentals 173 13.1 A Brief on Software Development Fundamentals 173 13.1.1 Requirements Phase 174 13.1.2 Design 174 13.1.3 Implementation 175 13.1.4 Integration and Testing 175 13.1.5 Operation and Maintenance 175 13.2 Hardware Platforms: Embedded System, Linux Versus PC 176 13.2.1 System Development Using Embedded System Board 176 13.2.2 System Development Using Multicore Hardware Platform 177 13.2.2.1 What Is a Core? 178 13.2.2.2 Network Element Development Using Multicore Platform 178 13.2.2.3 Runtime Choices of Multicore Processor 178 13.2.2.4 Software Programming Model for Multicore Processor 179 13.3 Selecting Software Platforms and Features 179 13.3.1 Selecting Available Data/Logical Structures 180 13.3.1.1 Advanced Data Structures 180 13.3.1.2 How Data Structure Affects the Application’s Performance 180 13.3.2 Selecting an Operating System Services/Facilities 181 13.3.2.1 Advance Features of Operating System: IPC 181 13.4 Software Simulators for a Mobile Communications Network 184 13.5 Software Root Causes and Their Debugging 185 13.5.1 Incorrect Usages of Software Library System Calls/APIs 185 13.5.2 Incorrect Usages of System Resources 185 13.5.3 Bad Software Programming Practices 185 13.6 Static Code Analysis of Software 186 13.7 Software Architecture and Software Organization 186 13.8 System and Software Requirements Analysis 188 13.9 Software Quality: Reliability, Scalability, and Availability 188 13.9.1 Reliability 188 13.9.2 Scalability 188 13.9.3 Availability 188 Chapter Summary 189 14 Protocols, Protocol Stack Developments, and Testing 191 14.1 Components of a 3GPP Protocol TS 191 14.2 3GPP Protocol Layer Structured Procedure Description 193 14.3 Protocol Layer Communications 194 14.3.1 Layer-to-Layer Communication Using Service Primitives 195 14.3.2 Layer-to-Layer Communication: SAP 196 14.3.3 Peer-to-Peer Layer Communication: PDU and Service Data Unit (SDU) 197 14.3.4 Types of PDU 198 14.3.5 Formats of PDU 198 14.4 Air Interface Message Format: Signaling Layer 3 198 14.4.1 A Brief on the Air Interface Layer 3 Protocol Stack 198 14.4.2 Classification of Layer 3 Messages 199 14.4.3 Layer 3 Protocol Header: Signaling Message Format 200 14.4.4 Layer 3 Protocol Header: Protocol Discriminator 202 14.4.5 Layer 3 Protocol Header: GSM, GPRS Skip Indicator 202 14.4.6 Layer 3 Protocol Header: GSM, GPRS Transaction Identifier 204 14.4.7 Layer 3 Protocol Header: LTE/EPS Bearer Identity 204 14.4.8 Layer 3 Protocol Header: 5GSM PDU Session Identity 204 14.4.9 Constructing a Layer 3 Message 204 14.4.10 Security Protected LTE/EPS and 5G NAS Layer MM Messages 205 14.4.11 Layer 3 Protocol Layer’s Message Dump 207 14.5 Air Interface Message Format: Layer 2 207 14.6 RAN – CN Signaling Messages 208 14.6.1 Protocol Layer Elementary Procedure 208 14.6.2 Types and Classes of EPs 210 14.6.3 EPs Code 210 14.6.4 Criticality of IE 211 14.6.5 Types of Protocol Errors and Its Handling 211 14.6.6 Choices of Triggering Message 212 14.6.7 Message Type 212 14.6.8 Message Description 212 14.6.9 Example: LTE/EPS S1 Interface: S1 Setup Procedure 213 14.7 Modes Operation of a Protocol Layer 213 14.8 Example of a Protocol Primitive and PDU Definition 215 14.9 Example of a Protocol Layer Frame Header Definition 216 14.10 Examples of System Parameters 216 14.11 Examples of Protocol Information Elements and Its Identifier 217 14.12 3GPP Release Specific Changes Implementation 218 14.13 Examples of Protocol Messages Types 219 14.14 Protocol Layer Timer Handling 219 14.15 Protocol Layer Development Using State Machine 222 14.16 Protocol Layer Development Using Message Passing 224 14.17 Protocol Layer Data and its Types 225 14.18 Protocol Layer Control and Configuration 226 14.19 Protocol Context Information 227 14.20 Protocol Layer Message Padding 228 14.21 Device Driver Development 229 14.22 Guidelines for Protocol Stack/Layer Development 230 14.23 Software Profiling, Tools and Performance Improvement 231 14.24 Protocol Stack Testing and Validation 231 Chapter Summary 233 15 Deriving Requirements Specifications from a TS 235 15.1 3GPP Protocol Layer Procedures 235 15.1.1 LTE UE Mode of Operation Requirements 236 15.1.2 LTE UE ATTACH Procedure Requirements 236 15.1.3 LTE UE DETACH Procedure Requirements 237 15.1.4 LTE UE Tracking Area Update Procedure Requirements 237 15.2 3GPP System Feature Development Requirements 238 15.2.1 Identification of System/Network Elements Interfaces Changes 238 15.2.2 Identifications of Impacts on Performance 238 15.2.3 Identifications of Impacts on Feature Management 239 15.2.4 Identification of Interworking Requirements with Existing Features 239 15.2.5 Charging and Accounting Aspects 239 15.3 Example Feature: Radio Access Network Sharing 239 15.3.1 Effects on Network Elements 239 15.3.2 Effects on Logical Interfaces 240 15.3.3 Selection of Core Network Operator: PLMN Id 241 15.4 Example: Interworking/Interoperations 242 15.4.1 Circuit-Switched Fall Back (CSFB) 242 15.4.2 Single Radio Voice Call Continuity (SRVCC) 243 15.5 3GPP System Feature and High-Level Design 244 Chapter Summary 245 Part IV 5G System and Network 247 16 5G Network: Use Cases and Architecture 249 16.1 5G System (5GS) Use Cases 249 16.1.1 Enablers and Key Principles of 5GS Use Cases 250 16.1.2 Other Enablers in 5G System 253 16.2 Support of Legacy Services by 5G System 253 16.3 5G System Network Architecture 254 16.3.1 3GPP Access Architecture 254 16.3.2 Non-3GPP Access Architecture 256 16.4 5G System NG–RAN/gNB Logical Architecture 256 16.5 5GC System Architecture Elements 259 16.6 5G System Deployment Solutions 260 16.6.1 E–UTRA–NR Dual Connectivity (EN–DC) for NSA Deployment 261 16.7 5G System and LTE/EPS Interworking 265 16.7.1 RAN-Level Interworking 265 16.7.2 Core Network (CN) Level Interworking: N26 Interface 265 16.7.2.1 Single Registration Mode with N26 Interface 266 16.7.2.2 Dual Registration Mode: Without N26 Interface 266 16.8 5G System Native and Mapped Network Identities 268 16.8.1 Mobility Area Identifiers 268 16.8.2 UE/Subscriber Permanent Identifiers 269 16.8.3 Core Network Identifiers 269 16.8.4 RAN Identifiers 269 16.8.5 Core Network Temporary Identities 270 16.9 5G System Network Slicing 270 16.9.1 Identities for a Network Slice 271 16.9.2 Impacts of Network Slicing Feature 273 16.10 Management and Orchestration (MANO) of 5G Network 278 16.11 5G System Security 280 16.11.1 UE Authentication Frameworks and Methods 280 16.11.2 Primary Authentication and Secondary Authentication 282 16.11.3 Key Hierarchy and Authentication Vector 282 16.11.4 New Security Requirements in 5G System 283 16.11.5 Subscriber Identities/Privacy Protection 286 Chapter Summary 287 17 Introduction to GSM, UMTS, and LTE Systems Air Interface 289 17.1 Air Interfaces Protocol Architectures 289 17.2 Protocol Sublayers 290 17.3 Control Plane and User Plane Protocols 291 17.4 Protocols Domains Classifications 291 17.5 Access Stratum and Non-access Stratum 291 17.6 Message Formats 292 17.7 Security Over the Air Interface 293 17.8 Piggybacking for Reduction of Signaling Overhead 293 17.8.1 Examples Piggybacking of Signaling Messages 293 Chapter Summary 294 18 5G NR Air Interface: Control Plane Protocols 295 18.1 NR Control Plane Protocol Layers 295 18.2 Session Management (5G SM) Layer 296 18.2.1 Procedures of 5G SM Layer 297 18.2.2 PDU Session Types 298 18.2.3 PDU Session Service Continuity (SSC) 299 18.2.4 PDU Sessions for Network Slices 300 18.2.5 Session Management (SM) Layer States 301 18.3 Quality of Service (5G QoS) 301 18.3.1 LTE/EPS QoS Model: EPS Bearer 301 18.3.2 5GS QoS Model: QoS Flow 301 18.3.3 GTP-U Plane Tunnel for PDU Session 302 18.3.4 Service Data Flow and PCC Rule 302 18.3.5 Binding of Service Data Flow 303 18.3.6 QoS Profile and QFI 303 18.3.7 QoS Rule and QRI 305 18.3.8 Mapping QoS Flow to Data Radio Bearer 305 18.3.9 Downlink Data Flow Through GTP-U Plane Tunnels 307 18.4 Mobility Management (5G MM) Layer 308 18.4.1 Mobility Area Concepts and Identifiers 308 18.4.2 Requirements of Mobility Management Functions 313 18.4.3 Functions and Procedures of 5G MM Layer 314 18.4.4 Mobility Management Layer States 315 18.4.5 Connection Management (CM) and Service Request 316 18.4.6 Mobility Pattern of UE 317 18.5 RRC Layer 317 18.5.1 Functions and Procedures of RRC Layer 317 18.5.2 System Information (SI) Broadcast 318 18.5.3 RRC Layer States 319 18.5.4 RRC INACTIVE State 320 18.5.5 Mobility of UE 326 18.5.5.1 UE Mobility in RRC IDLE State 326 18.5.5.2 UE Mobility in RRC INACTIVE State 326 18.5.5.3 UE Mobility in RRC CONNECTED State 327 18.5.6 Admission Control 332 Chapter Summary 334 19 5G NR Air Interface 335 19.1 NR User Plane Protocol Layers 335 19.2 SDAP Layer 336 19.3 PDCP Layer 336 19.4 RLC Layer 340 19.5 MAC Layer 342 19.5.1 Functions and Procedures 342 19.5.2 Scheduling Procedure 344 19.5.3 Random Access Procedure 346 19.5.4 Error Correction Through HARQ Procedure 351 19.5.5 Buffer Status Reporting (BSR) Procedure 352 19.5.6 Scheduling Request (SR) Procedure 353 19.5.7 Low Latency in the NR Due to Configured Scheduling 353 19.5.8 MAC Layer PDU and Header Structures 354 19.5.9 How MAC Layer Ensures Low‐Latency Requirements 356 19.5.10 Channel Structures in NR 357 19.6 Physical Layer 359 19.6.1 Principles of Transmissions and Its Directions 360 19.6.2 Physical Layer Functions, Procedures, and Services 360 19.6.3 OFDM Symbol 363 19.6.4 NR Frame and Slot Format 364 19.6.4.1 Subcarrier Spacing (SCS)/Numerologies (μ) 364 19.6.4.2 Slots per NR Frame and Subframe 364 19.6.4.3 Slot Formats in TDD Mode 366 19.6.4.4 Dynamic TDD 367 19.6.5 Resource Grid and Resource Block 368 19.6.5.1 Control Resource Set (CORESET) 369 19.6.5.2 Common Resource Blocks (CRB) 370 19.6.5.3 Physical Resource Block (PRB) 370 19.6.5.4 Virtual Resource Block (VRB) 370 19.6.5.5 Interleaved and Non‐interleaved PRB Allocation 370 19.6.5.6 PRB Bundling and VRB to PRB Mapping 371 19.6.5.7 Reference Point “A” 371 19.6.6 Channel and Transmission Bandwidths 371 19.6.7 Bandwidth Part (BWP) 373 19.6.7.1 Types of BWP 374 19.6.7.2 BWP Configuration 375 19.6.7.3 BWP Switching and Associated Delay 376 19.6.8 NR Resource Allocations 377 19.6.8.1 Frequency Domain Resource Allocation for FDD Transmission 377 19.6.8.2 Time‐Domain Resources Allocation for FDD Transmission 380 19.6.8.3 Time‐Domain Resources Allocation for TDD 383 19.6.9 Transport Channels and Their Processing Chain 384 19.6.9.1 CRC Calculation and its Attachment to a Transport Block 385 19.6.9.2 Code Block Segmentation 385 19.6.9.3 Channel Encoding with LDPC 386 19.6.9.4 Rate Matching and Concatenation 387 19.6.9.5 Multiplexing of UL‐SCH Data and Uplink Control Information 388 19.6.9.6 LDPC Encoding Examples 388 19.6.10 Physical Channels and Their Processing Chain 390 19.6.10.1 Physical Channels 390 19.6.10.2 Channel Mappings 391 19.6.10.3 Multiple Physical Antenna Transmissions 392 19.6.10.4 Physical Channel Processing Chain 395 19.6.10.5 Physical Downlink Control Channel (PDCCH) 397 19.6.10.6 Physical Uplink Control Channel (PUCCH) and Information (UCI) 404 19.6.11 Code Block Group‐Based Transmission and Reception 405 19.6.12 Physical Signals 409 19.6.12.1 Reference Signals Transmitted as Part of Physical Channels 410 19.6.12.2 Sounding Reference Signals 412 19.6.13 Downlink Synchronization 414 19.6.14 Millimeter Wave Transmission, Beamforming, and Its Management 419 19.6.15 Cell‐Level Radio Link Monitoring (RLM) 424 19.6.16 RRM Measurements for UE Mobility 426 19.6.16.1 RRM Measurement Signals and Their Quantities 426 19.6.16.2 RRM Measurements Framework 427 19.6.16.3 Overall RRM Process 429 19.6.17 Channel State Information (CSI) 430 19.6.18 Modulation and Coding Schemes (MCSs) 433 19.6.19 Link Adaptation Procedure 434 19.6.20 Random Access (RACH) Procedure 435 19.6.21 NR Radio Resources Management (RRM) Procedure 439 19.6.22 UE Transmit Power Control 444 19.6.22.1 Types of Power Control Procedure in NR 444 19.6.22.2 UE Transmit Power Determination Procedure in NR 445 19.6.23 Effect of Physical Layer on Data Throughputs 445 Chapter Summary 446 20 5G Core Network Architecture 447 20.1 Control Plane and User Plane Separation – CUPS 447 20.1.1 Impacts of CUPS Feature 448 20.1.2 CUPS in the LTE/EPC Network 449 20.1.3 CUPS Feature in 5G Core Network 450 20.2 Service-Based Architecture (SBA) 452 20.2.1 Network Functions and Its Instances 453 20.2.2 Network Functions (NFs) and Their Services Interfaces 454 20.2.3 5G System Architecture with NF 456 20.2.4 Network Functions and Their Services and Operations 457 20.2.5 Network Functions Services Framework 458 20.2.6 Services API for Network Functions 462 20.2.7 Network Function Selection 468 20.3 Network Function Virtualization (NFV) 469 Chapter Summary 472 21 5G System: Low-level Design 473 21.1 Design of 5GC Service Interface and Its Operations 473 21.2 Design of 5GC NF Service Interface Using UML and C++ Class Diagram 474 21.3 Usages of C++ Standard Template Library (STL) 475 21.4 Software Architecture for 5G System 476 21.4.1 NG-RAN Logical Nodes Software Architecture 476 21.4.2 5GC Software Architecture 479 21.5 Data Types Used in 5GC SBI Communications 479 Chapter Summary 491 22 3GPP Release 16 and Beyond 493 22.1 5GS Enhancements as Part of Release 16 493 22.2 5GS New Features as Part of Release 16 494 22.3 3GPP Release 17 496 Chapter Summary 496 Appendix 497 References 503 Index 507

Read more less

Book SynopsisUltra-Reliable and Low-Latency Communications (URLLC) Theory and Practice Comprehensive resource presenting important recent advances in wireless communications for URLLC services, including device-to-device communication, multi-connectivity, and more Ultra-Reliable and Low-Latency Communications (URLLC) Theory and Practice discusses the typical scenarios, possible solutions, and state-of-the-art techniques that enable URLLC in different perspectives from the physical layer to higher-level approaches, aiming to tackle URLLC's challenges with both theoretical and practical approaches, which bridges the lacuna between theory and practice. With long-term contributions to the development of future wireless networks, the text systematically presents a thorough study of the novel and innovative paradigm of URLLC; basic requirements are covered, along with essential definitions, state-of-the-art technologies, and promising research directions of URLLC. To aid in Table of ContentsPreface vii List of Contributors ix 1 URLLC: Faster, Higher, Stronger, and Together 1 Changyang She, Trung Q. Duong, Saeed R. Khosravirad, Petar Popovski, Mehdi Bennis, and Tony Q.S. Quek 2 Statistical Characterization of URLLC: Frequentist and Bayesian Approaches 15 Tobias Kallehauge, Pablo Ramirez-Espinosa, Anders E. Kalør, and Petar Popovski 3 Characterizing and Taming the Tail in URLLC 61 Chen-Feng Liu, Yung-Lin Hsu, Mehdi Bennis, and Hung-Yu Wei 4 Unsupervised Deep Learning for Optimizing Wireless Systems with Instantaneous and Statistic Constraints 85 Chengjian Sun, Changyang She, and Chenyang Yang 5 Channel Coding and Decoding Schemes for URLLC 119 Chentao Yue, Mahyar Shirvanimoghaddam, Branka Vucetic, and Yonghui li 6 Sparse Vector Coding for Ultra-reliable and Low-latency Communications 169 Byonghyo Shim 7 Network Slicing for URLLC 215 Peng Yang, Xing Xi, Tony Q. S. Quek, Jingxuan Chen, Xianbin Cao, and Dapeng Wu 8 Beamforming Design for Multi-user Downlink OFDMA-URLLC Systems 241 Walid R. Ghanem, Vahid Jamali, Yan Sun, and Robert Schober 9 A Full-Duplex Relay System for URLLC with Adaptive Self-Interference Processing 259 Hanjun Duan, Yufei Jiang, Xu Zhu, and Fu-Chun Zheng 10 Mobility Prediction for Reducing End-to-End Delay in URLLC 291 Zhanwei Hou, Changyang She, Yonghui Li, and Branka Vucetic 11 Relay Robot-Aided URLLC in 5G Factory Automation with Industrial IoTs 321 Dang Van Huynh, Saeed R. Khosravirad, Yuexing Peng, Antonino Masaracchia, and Trung Q. Duong Index 343

Read more less

Book SynopsisFrom 5G to 6G Understand the transition to the sixth generation of wireless with this bold introduction The transition from the fifth generation of wireless communication (5G) to the coming sixth generation (6G) promises to be one of the most significant phases in the history of telecommunications. The technological, social, and logistical challenges promise to be significant, and meeting these challenges will determine the future of wireless communication. Experts and professionals across dozens of fields and industries are beginning to reckon seriously with these challenges as the 6G revolution approaches. From 5G to 6G provides an overview of this transition, offering a snapshot of a moment in which 5G is establishing itself and 6G draws ever nearer. It focuses on recent advances in wireless technology that brings 6G closer to reality, as well as the near-term challenges that still have to be met for this transition to succeed. The result is an essential book for anyone wishing to understand the future of wireless telecommunications in an increasingly connected world. From 5G to 6G readers will also find: 6G applications to both AI and Machine Learning, technologies which loom ever larger in wireless communicationDiscussion of subjects including smart healthcare, cybersecurity, extended reality, and moreTreatment of the ongoing infrastructural and technological requirements for 6G From 5G to 6G is essential for researchers and academics in wireless communication and computer science, as well as for undergraduates in related subjects and professionals in wireless-adjacent fields.Table of ContentsAbout the Author xiii Preface xv 1 Technologies and Development for the Next Information Age 1 1.1 Introduction 1 1.2 Roadmap to 6G 1 1.2.1 Society 5.0 4 1.2.2 Extended Reality 4 1.2.3 Wireless Brain-Computer 5 1.2.4 Haptic Communication 5 1.2.5 Smart Healthcare 5 1.2.6 Five-Sense Information 6 1.2.7 The Internet of Everything 6 1.2.8 5G to 6G 6 1.3 AI and Cybersecurity: Paving the Way for the Future 10 1.4 Fusion of IoT, AI, and Cybersecurity 10 1.4.1 Where Did AI Begin? 12 1.4.2 Role of AI 12 1.4.3 Disadvantages of AI 12 1.4.4 Advantages of AI 12 1.4.5 Threats from Hackers 14 1.5 How AI Can Help Solve These Problems 15 1.6 Connected Devices and Cybersecurity 16 1.7 Solutions for Data Management in Cybersecurity 17 1.8 Conclusion 17 References 18 2 Networks of the Future 21 2.1 Introduction 21 2.2 The Motive for Energy-Efficient ICTs 22 2.2.1 Approaches 23 2.3 Wireless Networks 24 2.3.1 Wi-Fi 26 2.3.2 Lte 28 2.3.3 Heterogeneous Networks 29 2.3.4 Femtocell Repeater 29 2.3.5 The Dawn of 5G Wireless Systems 30 2.3.6 Advancing from 5G to 6G Networks 32 2.4 Cognitive Networking 33 2.4.1 Zero-Touch Network and Service Management 34 2.4.2 Zero-Trust Networking 35 2.4.3 Information-Centric Networking 35 2.4.3.1 Basic Concepts of ICN 36 2.4.4 In-Network Computing 36 2.4.5 Active Networking 36 2.5 Mobile Edge Computing 37 2.6 Quantum Communications 37 2.6.1 Quantum Computing and 6G Wireless 38 2.7 Cybersecurity of 6G 38 2.8 Massive Machine-Type Communications (MTC) 39 2.9 Edge-Intelligence and Pervasive Artificial Intelligence in 6G 40 2.10 Blockchain: Foundations and Role in 6G 40 2.11 Role of Open-Source Platforms in 6G 40 2.11.1 PHY Technologies for 6G Wireless 40 2.11.2 Reconfigurable Intelligent Surface for 6G Wireless Networks 41 2.11.3 Millimeter-Wave and Terahertz Spectrum for 6G Wireless 41 2.11.4 Challenges in Transport Layer for Terabit Communications 41 2.11.5 High-Capacity Backhaul Connectivity for 6G Wireless 42 2.11.6 Cloud-Native Approach for 6G Wireless Networks 42 2.11.7 Machine Type Communications in 6G 42 2.11.8 Impact of 5G and 6G on Health and Environment 42 2.12 Integration of 5G with AI and IoT and Roadmap to 6G 43 2.13 3gpp 47 2.14 Conclusion 49 References 49 3 The Future of Wireless Communication with 6G 53 3.1 Introduction 53 3.2 Recent Trends Leading to 6G Technology Evolution 53 3.3 Security and Privacy Challenges in 6G Wireless Communications 53 3.4 The Impact of 6G on Healthcare Systems 56 3.5 The Impact of 6G on Space Technology and Satellite Communication 58 3.6 The Impact of 6G on Other Industries 60 3.7 Terahertz Wireless Systems and Networks with 6G 61 3.8 The Future of 6G and Its Role in IT 62 References 62 4 Artificial Intelligence and Machine Learning in the Era of 5G and 6G Technology 65 4.1 Artificial Intelligence and Machine Learning: Definitions, Applications, and Challenges 66 4.1.1 Application of Machine Learning and Artificial Intelligence 66 4.1.2 Challenges for Machine Learning and Artificial Intelligence 66 4.2 Artificial Intelligence: Laws, Regulations, and Ethical Issues 67 4.2.1 Ethical Governance in Artificial Intelligence 67 4.2.2 The Future of Regulation for AI 67 4.3 Potentials of Artificial Intelligence in Wireless 5G and 6G: Benefits and Challenges 68 4.3.1 Artificial Intelligence in Wireless 5G and 6G 68 4.3.2 Benefits and Challenges of AI in 5G and 6G 68 4.3.3 How Can AI Be Used to Enhance 6G Wireless Security? 68 4.3.4 The 6G Era’s Edge Intelligence and Cloudification 69 4.3.5 Distributed Artificial Intelligence in 6G Security 69 4.4 Cybersecurity Issues in Advanced 5G and 6G 70 4.5 Benefits and Challenges of Using AI in Cybersecurity: Help or Hurt? 70 4.6 How Can AI Be Used by Hackers Attacking Networks? 71 4.7 Conclusion 72 References 72 5 6G Wireless Communication Systems: Emerging Technologies, Architectures, Challenges, and Opportunities 73 5.1 Introduction 73 5.2 Important Aspects of Sixth-Generation Communication Technology 73 5.2.1 A Much Higher Data Rate 74 5.2.2 A Much Lower Latency 74 5.2.3 Network Reliability and Accuracy 74 5.2.4 Energy Efficiency 74 5.2.5 Focus on Machines as Primary Users 74 5.2.6 AI Wireless Communication Tools 74 5.2.7 Personalized Network Experience 74 5.3 Enabling Technologies Behind the Drive for 6G 76 5.3.1 Artificial Intelligence 76 5.3.2 Terahertz Communications 78 5.3.3 Optical Wireless Technology 78 5.4 Extreme Performance Technologies in 6G Connectivity 79 5.4.1 Quantum Communication and Quantum ml 79 5.4.2 Blockchain 80 5.4.2.1 Internal Network Operations 80 5.4.2.2 Ecosystem for Productive Collaboration 80 5.4.2.3 Tactile Internet 80 5.4.2.4 Spectrum Sharing (FDSS) and Free Duplexing 80 5.5 6G Communications Using Intelligent Platforms 81 5.5.1 Integrated Intelligence 82 5.5.2 Satellite-Based Integrated Network 82 5.5.3 Wireless Information and Energy Transfer Are Seamlessly Integrated 83 5.6 Artificial Intelligence and a Data-Driven Approach to Networks 83 5.6.1 Zero-Touch Network 84 5.6.2 AI by Design 85 5.6.3 Technological Fundamentals for Zero-Touch Systems 85 5.7 Sensing for 6G 85 5.7.1 A Bandwidth as Well as Carrier Frequency Rise 85 5.7.2 Chip Technologies of the Future 86 5.7.3 Models of Consistent Channels 86 5.7.4 X-Haul and Transport Network for 6G 87 5.8 Applications 87 5.9 Innovative 6G Network Architectures 89 5.10 Conclusion 89 References 90 6 6G: Architecture, Applications, and Challenges 91 6.1 Introduction 91 6.2 6G Network Architecture Vision 93 6.2.1 6G Use Cases, Requirements, and Metrics 94 6.2.2 What 5G Is Currently Covering 95 6.3 6th Generation Networks: A Step Beyond 5G 97 6.3.1 6G and the Fundamental Features 98 6.4 Emerging Applications of 6G Wireless Networks 99 6.4.1 Virtual, Augmented, and Mixed Reality 99 6.4.2 Holographic Telepresence 100 6.4.3 Automation: The Future of Factories 101 6.4.4 Smart Lifestyle with the Integration of the Internet of Things 101 6.4.5 Autonomous Driving and Connected Devices 101 6.4.6 Healthcare 101 6.4.7 Nonterrestrial Communication 101 6.4.8 Underwater Communication 102 6.4.9 Disaster Management 102 6.4.10 Environment 102 6.5 The Requirements and KPI Targets of 6G 102 6.5.1 Extremely Low Latency 102 6.5.2 Low Power Consumption 102 6.5.3 High Data Rates 103 6.5.4 High-Frequency Bands 103 6.5.5 Ultra-Reliability 103 6.5.6 Security and Privacy 103 6.5.7 Massive Connection Density 104 6.5.8 Extreme Coverage Extension 104 6.5.9 Mobility 104 6.6 6G Applications 104 6.7 Challenges in 6G: Standardization, Design, and Deployment 104 References 106 7 Cybersecurity in Digital Transformation Era: Security Risks and Solutions 109 7.1 Introduction 109 7.2 Digital Transformation and Mesh Networks of Networks 109 7.3 Security as the Enemy of Digital Transformation 111 7.4 The Current State of Cybercrime 113 7.5 Security and Technologies of the Digital Transformation Economy 115 7.6 Tackling the Cybersecurity Maturity Challenges to Succeed with Digital Transformation 116 7.7 Security Maturity and Optimization: Perception versus Reality 117 7.7.1 Why Cybersecurity Maturity Is Not What It Should Be in the Digital Business and Transformation Reality 118 7.7.2 Why Cybersecurity Maturity and Strategy Are Lagging 119 7.8 Changing Security Parameters and Cyber Risks Demand a Holistic Security Approach for Digital Business 120 7.9 Cybersecurity Challenges and Digital Risks for the Future 121 7.10 Conclusion 122 References 122 8 Next Generations Networks: Integration, Trustworthiness, Privacy, and Security 125 8.1 Introduction 125 8.2 The State of 5G Networks 127 8.2.1 Applications and Services of 5G Technologies 128 8.3 6G: Key Technologies 130 8.4 6G: Application and Services 134 8.5 Benefits of 6G over 5G: A Comparison 135 8.5.1 Artificial Intelligence in 5G and 6G: Benefits and Challenges 135 8.5.2 Artificial Intelligence and Cybersecurity 136 8.5.3 Benefits and Challenges of AI and 6G for Cybersecurity as Defense and Offense 136 8.6 6G: Integration and Roadmap 137 8.7 Key Words in Safeguarding 6G 137 8.7.1 Trust 137 8.7.2 Security 137 8.7.3 Privacy 138 8.8 Trustworthiness in 6G 138 8.8.1 Is Trust Networking Needed? 138 8.8.2 Benefits of Trust Networking for 6G 138 8.8.3 Constraints of Trust Networking in 6G 138 8.8.4 Principles for Trust Networking 139 8.8.5 Challenges in Trust Networking for 6G 139 8.9 Network Security Architecture for 6G 140 8.9.1 Privacy and Security in IoT for 6G 140 8.10 6G Wireless Systems 141 8.10.1 Advances 141 8.10.2 Physical Layer Security as a Means of Confidentiality 142 8.10.3 Challenges of Implementing Federated Learning 143 8.10.4 Physical Layer Security for Six-Generation Connectivity 143 8.10.5 Physical Layer Security Using Light Communications 144 8.10.6 Challenges for Physical Layer Security 144 8.10.7 Privacy Requirements for 6G 145 8.10.8 Is Personal Information Really Personal? 145 8.11 Fifth Generation vs. Sixth Generation 145 8.12 Conclusion 146 References 147 9 Artificial Intelligence: Cybersecurity and Security Threats 149 9.1 Introduction 149 9.2 5G and 6G 150 9.3 Cybersecurity in Its Current State 151 9.4 AI as a Concept 153 9.5 AI: A Solution for Cybersecurity 154 9.6 AI: New Challenges in Cybersecurity 154 9.7 Conclusion 156 References 156 10 Impact of Artificial Intelligence and Machine Learning on Cybersecurity 159 10.1 Introduction 159 10.2 What Is Artificial Intelligence (AI)? 160 10.2.1 Reactive Machines 160 10.2.2 Limited Memory 160 10.2.3 Theory of Mind 160 10.2.4 Self-Awareness 161 10.3 The Transformative Power of AI 161 10.4 Understanding the Relationship Between AI and Cybersecurity 161 10.5 The Promise and Challenges of AI for Cybersecurity 162 10.5.1 Risks and Impacts of AI on Cybersecurity (Threats and Solutions) 163 10.5.1.1 Domestic Risks 164 10.5.1.2 Local Risks 164 10.5.1.3 National Risks 164 10.5.1.4 Why Prediction and Prevention 164 10.6 Broad Domain of AI Security (Major Themes in the AI Security Landscape) 164 10.6.1 Digital/Physical 165 10.6.2 Protection from Malicious Use of AI and Automated Cyberattacks 165 10.6.3 Other Technologies with AI and Their Integration 165 10.6.4 Political 165 10.6.5 Manipulation and Disinformation Protection 165 10.6.6 Infrastructure Based on AI and Digital Expertise of Government 166 10.6.6.1 Economic 166 10.6.6.2 Labor Displacement and Its Mitigation 166 10.6.6.3 Promotion of AI R&D 166 10.6.6.4 Education and Training That Is Updated 167 10.7 Transparency of Artificial Intelligence and Accountability Societal Aspects 167 10.7.1 Rights of Privacy and Data 167 10.8 Global AI Security Priorities 168 10.8.1 Global Economy 168 10.8.2 Global Privacy and Data Rights 168 10.8.2.1 AI and Ethics 169 10.8.3 Automation of Cyberattacks or Social Engineering Attacks 170 10.8.4 Target Prioritizing with Machine Learning 170 10.9 Automation of Services in Cybercriminal Offense 170 10.9.1 Increased Scale of Attacks 170 10.10 The Future of AI in Cybersecurity 171 10.11 Conclusion 171 References 172 11 AI and Cybersecurity: Paving the Way for the Future 175 11.1 Introduction 175 11.2 IoT Security and the Role of AI 176 11.3 Cybercrime and Cybersecurity 179 11.4 How Can AI Help Solve These Problems? 181 11.5 The Realm of Cyberspace 181 11.6 Connected Devices and Cybersecurity 182 11.7 Solutions for Data Management in Cybersecurity 183 11.8 Conclusion 183 References 184 12 Future 6G Networks 185 12.1 Introduction 185 12.2 Vision, Challenges, and Key Features for Future 6G Networks 186 12.2.1 Fourth Generation Long-Term Evolution (4G-LTE) 187 12.3 Rationale for 6G Networks with Prevailing and Future Success of 5G 188 12.4 Missing Units from LTE and 5G That 6G Will Integrate 189 12.5 Features of 6G Networks 189 12.5.1 Large Bandwidth 189 12.5.2 Artificial Intelligence 189 12.5.3 Operational Intelligence 190 12.6 Wireless Networks 190 12.6.1 Beyond 5G and Toward 6G 190 12.6.2 Visible-Light Communications 191 12.6.3 E-MBB Plus 191 12.6.4 Big Communications 191 12.6.5 Secure Ultra-Reliable Low-Latency Communications 192 12.6.6 Three-Dimensional Integrated Communications 192 12.6.7 Underwater Communication 193 12.6.8 Space Communication 194 12.6.9 UAV-Based Communication 194 12.6.10 Unconventional Data Communications 194 12.6.11 Tactical Communications 195 12.6.12 Holographic Communications 195 12.6.13 Human-Bond Communications 196 12.7 Challenges for 6G Networks 196 12.7.1 Potential Health Issues 196 12.7.2 Security and Privacy Concerns 197 12.7.3 Research Activities and Trends 197 12.8 Conclusion 198 References 200 Index 203

Read more less

Book SynopsisOpen RAN A comprehensive survey of Open RAN technology and its ecosystem In Open RAN: The Definitive Guide, a team of distinguished industry leaders deliver an authoritative guide to all four principles of the Open RAN vision: openness, virtualization, intelligence, and interoperability. Written by the industry experts currently defining the specifications, building the systems, and testing and deploying the networks, the book covers O-RAN architecture, the fronthaul interface, security, cloudification, virtualization, intelligence, certification, badging, and standardization. This critical reference on Open RAN explains how and why an open and disaggregated, intelligent, and fully virtualized network is the way networks should be designed and deployed moving forward. Readers will also find: A thorough introduction from key industry players, including AT&T, Telefonica, Mavenir, VMWare, Google and VIAVI Comprehensive explorations of Open X-Table of ContentsList of Contributors xiii Foreword xv Preface xvii About the Authors xix Definitions / Acronyms xxi 1 The Evolution of RAN 1 Sameh M. Yamany 1.1 Introduction 1 1.2 RAN Architecture Evolution 4 1.2.1 The 2G RAN 5 1.2.2 The 3G RAN 6 1.2.3 The 4G/LTE RAN 6 1.2.4 The 5G RAN 9 1.3 The Case for Open RAN 11 1.4 6G and the Road Ahead 11 1.5 Conclusion 13 Bibliography 13 2 Open RAN Overview 14 Rittwik Jana 2.1 Introduction 14 2.1.1 What is Open RAN and Why is it Important? 17 2.1.2 How Does Open RAN Accelerate Innovation? 17 2.1.3 What are the major challenges that Open RAN can help to address? 18 2.2 Open RAN Architecture 18 2.3 Open RAN Cloudification and Virtualization 19 2.4 RAN Intelligence 20 2.5 Fronthaul Interface and Open Transport 20 2.6 Securing Open RAN 21 2.7 Open Source Software 21 2.8 RAN Automation and Deployment with CI/CD 22 2.9 Open RAN Testing 22 2.10 Industry Organizations 23 2.11 Conclusion 23 Bibliography 23 3 O-RAN Architecture Overview 24 Rajarajan Sivaraj and Sridhar Rajagopal 3.1 Introduction 24 3.1.1 General Description of O-RAN Functions 24 3.1.1.1 Centralized Unit – Control Plane and User Plane Functions (CU-CP and CU-UP) 26 3.1.1.2 Distributed Unit Function (DU) 26 3.1.1.3 Radio Unit Function (RU) 26 3.1.1.4 Evolved Node B (eNB) 27 3.1.2 RAN Intelligent Controller (RIC) and Service Management and Orchestration (SMO) Functions 28 3.1.3 Interfaces 29 3.2 Near-RT RIC Architecture 30 3.2.1 Standard Functional Architecture Principles 30 3.2.2 E2 Interface Design Principles 32 3.2.3 xApp API Design Architecture 34 3.3 Non-RT RIC Architecture 37 3.3.1 Standard Functional Architecture Principles 38 3.3.2 A1 Interface Design Principles 38 3.3.3 R1 API Design Principles for rApps 41 3.4 SMO Architecture 47 3.4.1 Standard Functional Architecture Principles 47 3.4.2 O1 Interface Design Principles 48 3.4.3 Open M-Plane Fronthaul Design Principles 51 3.4.4 O2 Interface Design Principles 52 3.5 Other O-RAN Functions and Open Interfaces 54 3.5.1 O-RAN compliant Centralized Unit Control Plane (O-CU-CP) 54 3.5.1.1 Control Plane Procedures 54 3.5.1.2 Management Plane Procedures 54 3.5.2 O-CU-UP 54 3.5.2.1 Control Plane Procedures 55 3.5.2.2 User Plane Procedures 55 3.5.2.3 Management Plane Procedures 55 3.5.3 O-DU 55 3.5.3.1 Control Plane Procedures 55 3.5.3.2 User Plane Procedures 55 3.5.3.3 Management Plane Procedures 55 3.5.4 O-eNB 56 3.5.5 O-RU 56 3.6 Conclusion 57 Bibliography 57 4 Cloudification and Virtualization 59 Padma Sudarsan and Sridhar Rajagopal 4.1 Virtualization Trends 59 4.2 Openness and Disaggregation with vRAN 59 4.3 Cloud Deployment Scenarios 61 4.3.1 Private, Public, and Hybrid Cloud 61 4.3.2 Telco Features Required for “Any Cloud” Deployment 62 4.3.3 On Premise, Far Edge, Edge, and Central Deployments 63 4.3.4 Classical, Virtual Machines (VMs), Containers, and Hybrid Deployments 64 4.4 Unwinding the RAN Monolith 64 4.4.1 Adapting Cloud-Native Principles 66 4.4.2 Architectural Patterns 67 4.4.3 Software Architecture Portability and Refactoring Considerations 68 4.4.4 Compute Architecture Consideration 69 4.5 Orchestration, Management, and Automation as Key to Success 70 4.5.1 Acceleration Abstraction Layer 73 4.5.2 Cloud Deployment Workflow Automation 75 4.6 Summary 76 Bibliography 76 5 RAN Intelligence 77 Dhruv Gupta, Rajarajan Sivaraj, and Rittwik Jana 5.1 Introduction 77 5.2 Challenges and Opportunities in Building Intelligent Networks 77 5.3 Background on Machine Learning Life Cycle Management 78 5.4 ML-Driven Intelligence and Analytics for Non-RT RIC 80 5.5 ML-Driven Intelligence and Analytics for Near-RT RIC 82 5.6 E2 Service Models for Near-RT RIC 83 5.6.1 E2SM-KPM 84 5.6.2 E2SM-RC 84 5.6.3 Other E2SMs 85 5.7 ml Algorithms for Near-RT RIC 86 5.7.1 Reinforcement Learning Models 87 5.8 Near-RT RIC Platform Functions for AI/ML Training 88 5.9 RIC Use Cases 89 5.10 Conclusion 90 Bibliography 90 6 The Fronthaul Interface 91 Aditya Chopra 6.1 The Lower-Layer Split RAN 91 6.1.1 Lower Layer Fronthaul Split Options 92 6.2 Option 8 Split – CPRI and eCPRI 93 6.3 Option 6 Split – FAPI and nFAPI 94 6.3.1 Subinterfaces 97 6.3.2 Architecture Agnostic Deployment 97 6.4 Option 7 Split – O-RAN Alliance Open Fronthaul 97 6.4.1 Control (C) and User (U) Plane 98 6.4.2 Management (M) Plane 98 6.4.3 Synchronization (S) Plane 100 6.4.4 Key Features 100 6.4.4.1 Fronthaul Compression 100 6.4.4.2 Delay Management 102 6.4.4.3 Beamforming 102 6.4.4.4 Initial Access 103 6.4.4.5 License Assisted Access and Spectrum Sharing 104 6.5 Conclusions 104 Bibliography 104 7 Open Transport 105 Reza Vaez-Ghaemi and Luis Manuel Contreras Murillo 7.1 Introduction 105 7.2 Requirements 105 7.2.1 Fronthaul Requirements 106 7.2.2 Midhaul Requirements 106 7.2.3 Backhaul Requirements 107 7.2.4 Synchronization Requirements 107 7.3 WDM Solutions 108 7.3.1 Passive WDM 109 7.3.2 Active WDM 109 7.3.3 Semiactive WDM 110 7.4 Packet-Switched Solutions 111 7.4.1 Technology Overview 112 7.4.2 Deployment Patterns 112 7.4.3 Connectivity Service and Protocols 113 7.4.4 Quality of Service (QoS) 114 7.5 Management and Control Interface 114 7.5.1 Control and Management Architecture 114 7.5.2 Interaction with O-RAN Management 116 7.6 Synchronization Solutions 117 7.6.1 Synchronization Baseline 117 7.6.2 Synchronization Accuracy and Limits 118 7.7 Testing 118 7.8 Conclusion 119 Bibliography 120 8 O-RAN Security 121 Amy Zwarico 8.1 Introduction 121 8.2 Zero Trust Principles 121 8.3 Threats to O-RAN 122 8.3.1 Stakeholders 122 8.3.2 Threat Surface and Threat Actors 122 8.3.3 Overall Threats 123 8.3.4 Threats Against the Lower Layer Split (LLS) Architecture and Open Fronthaul Interface 123 8.3.5 Threats Against O-RU 124 8.3.6 Threats Against Near- and Non-Real-Time RICs, xApps, and rApps 124 8.3.7 Threats Against Physical Network Functions (PNFs) 124 8.3.8 Threats Against SMO 125 8.3.9 Threats Against O-Cloud 125 8.3.10 Threats to the Supply Chain 125 8.3.11 Physical Threats 126 8.3.12 Threats Against 5G Radio Networks 126 8.3.13 Threats to Standards Development 126 8.4 Protecting O-RAN 126 8.4.1 Securing the O-RAN-Defined Interfaces 126 8.4.1.1 A1 127 8.4.1.2 O1 127 8.4.1.3 O2 128 8.4.1.4 E2 128 8.4.1.5 Open Fronthaul 128 8.4.1.6 R1 130 8.4.1.7 3GPP Interfaces 131 8.4.2 Securing the O-Cloud 131 8.4.3 Container Security 131 8.4.4 O-RAN Software Security 131 8.4.5 Software Bill of Materials (SBOM) 132 8.5 Recommendations for Vendors and MNOs 132 8.6 Conclusion 134 Bibliography 134 9 Open RAN Software 137 David Kinsey, Padma Sudarsan, and Rittwik Jana 9.1 Introduction 137 9.2 O-RAN Software Community (OSC) 138 9.2.1 OSC Projects 138 9.2.2 The Service Management and Orchestration (SMO) Framework 138 9.2.3 Near-RT RIC (RIC) 139 9.2.4 O-CU-CP and O-CU-UP 140 9.2.5 O-DU Project 140 9.2.6 O-RU 140 9.2.7 O-Cloud 140 9.2.8 The AI/ML Framework 141 9.2.9 Support Projects 141 9.3 Open Network Automation Platform (ONAP) 141 9.3.1 Netconf/YANG Support 141 9.3.2 Configuration Persistence 142 9.3.3 VES Support 142 9.3.4 A1 Support 142 9.3.5 Optimization Support 142 9.4 Other Open-Source Communities 143 9.5 Conclusion 144 Bibliography 144 10 Open RAN Deployments 145 Sidd Chenumolu 10.1 Introduction 145 10.2 Network Architecture 146 10.2.1 Network Components 147 10.2.1.1 Antenna 147 10.2.1.2 O-RAN – Radio Unit 148 10.2.1.3 O-RAN-Distributed Unit (O-DU) 150 10.2.1.4 O-RAN-Centralized Unit (O-CU) 150 10.2.1.5 RAN Intelligent Controller (RIC) 150 10.2.2 Traditional vs. O-RAN Deployment 151 10.2.3 Typical O-RAN Deployment 152 10.2.4 Spectrum and Regulatory 153 10.3 Network Planning and Design 153 10.3.1 Cell Site Design 154 10.3.2 Network Function Placement 155 10.3.3 Dimensioning 155 10.3.3.1 Application Dimensioning 155 10.3.3.2 Platform Dimensioning 156 10.3.4 Virtualization Impact 156 10.3.4.1 Non-Uniform Memory Access 157 10.3.4.2 Hyper-Threading 157 10.3.4.3 CPU Pinning 157 10.3.4.4 Huge Page 157 10.3.4.5 Single Root Input/Output Virtualization 158 10.3.4.6 PCI Passthrough 158 10.3.4.7 Data Plane Development Kit 158 10.3.4.8 Resource Director Technology 158 10.3.4.9 Cache Allocation Technology 158 10.3.4.10 Resource Overcommitment 159 10.3.4.11 Operating System 159 10.3.4.12 K8S Impact 159 10.3.5 Networking Hardware 159 10.3.6 Hardware Type 160 10.3.7 Reliability and Availability 160 10.3.8 Impact of Network Slicing 161 10.4 Network Deployment 162 10.4.1 DU Deployment 162 10.4.1.1 DU Deployed at a Centralized Data Center 162 10.4.1.2 Timing Design When DU is at the dc 163 10.4.1.3 DU Deployed at Cell Site 164 10.4.2 CU Deployment 165 10.4.3 Radio Unit Instantiation 165 10.4.4 Radio Unit Management 166 10.4.4.1 Hierarchical Management Architecture Model 166 10.4.4.2 Hybrid Management Architecture Model 166 10.4.5 Network Management 166 10.4.6 Public Cloud Provider Overview 167 10.4.6.1 Native Services 167 10.4.6.2 CD Pipeline 167 10.4.6.3 Cluster Creation and Management 168 10.4.6.4 Transport Design 168 10.4.7 Life Cycle Management of NFs 168 10.4.8 Network Monitoring and Observability 169 10.4.8.1 Prometheus 169 10.4.8.2 Jaeger 169 10.4.8.3 Fluentd and Fluentbit 169 10.4.8.4 Probing 169 10.4.9 Network Inventory 169 10.4.10 Building the Right Team 170 10.5 Conclusion 170 Bibliography 170 11 Open RAN Test and Integration 172 Ian Wong, Ph.D. 11.1 Introduction 172 11.2 Testing Across the Network Life Cycle 174 11.3 O-RAN ALLIANCE Test and Integration Activities 175 11.3.1 Test Specifications 175 11.3.2 Conformance Test Specifications 176 11.3.2.1 A1 Interface Test Specification (O-RAN.WG2.A1TS) 178 11.3.2.2 E2 Interface Test Specification (O-RAN.WG3.E2TS) 179 11.3.2.3 Open Fronthaul Conformance Test Specification (O-RAN.WG4.CONF) 180 11.3.2.4 Xhaul Transport Testing (O-RAN.WG9.XTRP-Test.0) 181 11.3.2.5 Security Test Specifications (O-RAN.SFG.Security-Test-Specifications) 181 11.3.3 Interoperability Test Specifications 181 11.3.3.1 Fronthaul Interoperability Test Specification (O-RAN.WG4.IOT.0-09.00) 182 11.3.3.2 Open F1/W1/E1/X2/Xn Interoperability Test Specification (O-RAN.WG5.IOT.0) 183 11.3.3.3 Stack Interoperability Test Specification (O-RAN.WG8.IOT) 183 11.3.4 End-to-End Test Specifications 185 11.3.5 O-RAN Certification and Badging 186 11.3.6 Open Test and Integration Centers 187 11.3.7 O-RAN Global PlugFests 189 11.4 Conclusion 189 Bibliography 189 12 Other Open RAN Industry Organizations 191 Aditya Chopra, Manish Singh, Prabhakar Chitrapu, Luis Lopes, and Diane Rinaldo 12.1 Telecom Infra Project 191 12.1.1 Organizational Structure 192 12.1.2 Core Activities 194 12.2 Trials and Deployments 194 12.3 Small Cell Forum 195 12.3.1 A History of Openness at SCF 196 12.3.2 Alignment with the 3GPP and O-RAN Alliance Solutions 196 12.4 3rd Generation Partnership Project 197 12.5 Open RAN Policy Coalition 199 12.6 Conclusion 200 Bibliography 200 Index 201

Read more less

Book SynopsisINTELLIGENT SURFACES EMPOWERED 6G WIRELESS NETWORK Integrate intelligent surfaces into the wireless networks of the future. The next generation of wireless technology (6G) promises to transform wireless communication and human interconnectivity like never before. Intelligent surface, which adopts significant numbers of small reflective surfaces to reconfigure wireless connections and improve network performance, has recently been recognized as a critical component for enabling future 6G. The next phase of wireless technology demands engineers and researchers are familiar with this technology and are able to cope with the challenges. Intelligent Surfaces Empowered 6G Wireless Network provides a thorough overview of intelligent surface technologies and their applications in wireless networks and 6G. It includes an introduction to the fundamentals of intelligent surfaces, before moving to more advanced content for engineers who understand them and look to apply them in the 6G realm. Its dTable of ContentsAbout the Editors xiii List of Contributors xv Preface xxi Acknowledgement xxiii Part I Fundamentals of IRS 1 1 Introduction to Intelligent Surfaces 3Kaitao Meng, Qingqing Wu, Trung Q. Duong, Derrick Wing Kwan Ng, Robert Schober, and Rui Zhang 1.1 Background 3 1.2 Concept of Intelligent Surfaces 5 1.3 Advantages of Intelligence Surface 7 1.4 Potential Applications 8 1.5 Conclusion 12 2 IRS Architecture and Hardware Design 15Zijian Zhang, Yuhao Chen, Qiumo Yu, and Linglong Dai 2.1 Metamaterials: Basics of IRS 15 2.2 Programmable Metasurfaces 16 2.3 IRS Hardware Design 18 2.4 State-of-the-Art IRS Prototype 23 3 On Path Loss and Channel Reciprocity of RIS-Assisted Wireless Communications 37 Wankai Tang, Jinghe Wang, Jun Yan Dai, Marco Di Renzo, Shi Jin, Qiang Cheng, and Tie Jun Cui 3.1 Introduction 37 3.2 Path Loss Modeling and Channel Reciprocity Analysis 39 3.3 Path Loss Measurement and Channel Reciprocity Validation 47 3.4 Conclusion 54 4 Intelligent Surface Communication Design: Main Challenges and Solutions 59Kaitao Meng, Qingqing Wu, and Rui Zhang 4.1 Introduction 59 4.2 Channel Estimation 59 4.3 Passive Beamforming Optimization 65 4.4 IRS Deployment 73 4.5 Conclusion 79 Part II IRS for 6G Wireless Systems 83 5 Overview of IRS for 6G and Industry Advance 85Ruiqi (Richie) Liu, Konstantinos D. Katsanos, Qingqing Wu, and George C. Alexandropoulos 5.1 IRS for 6G 85 5.2 Industrial Progresses 98 6 RIS-Aided Massive MIMO Antennas 117Stefano Buzzi, Carmen D'Andrea, and Giovanni Interdonato 6.1 Introduction 117 6.2 System Model 119 6.3 Uplink/Downlink Signal Processing 123 6.4 Performance Measures 126 6.5 Optimization of the RIS Phase Shifts 128 6.6 Numerical Results 130 6.7 Conclusions 134 7 Localization, Sensing, and Their Integration with RISs 139George C. Alexandropoulos, Hyowon Kim, Jiguang He, and Henk Wymeersch 7.1 Introduction 139 7.2 RIS Types and Channel Modeling 142 7.3 Localization with RISs 147 7.4 Sensing with RISs 154 7.5 Conclusion and Open Challenges 159 8 IRS-Aided THz Communications 167Boyu Ning and Zhi Chen 8.1 IRS-Aided THz MIMO System Model 167 8.2 Beam Training Protocol 168 8.3 IRS Prototyping 175 8.4 IRS-THz Communication Applications 182 9 Joint Design of Beamforming, Phase Shifting, and Power Allocation in a Multi-cluster IRS-NOMA Network 187Ximing Xie, Fang Fang, and Zhiguo Ding 9.1 Introduction 187 9.2 System Model and Problem Formulation 190 9.3 Alternating Algorithm 193 9.4 Simulation Result 200 9.5 Conclusion 203 10 IRS-Aided Mobile Edge Computing: From Optimization to Learning 207Xiaoyan Hu, Kai-Kit Wong, Christos Masouros, and Shi Jin 10.1 Introduction 207 10.2 System Model and Objective 208 10.3 Optimization-Based Approaches to IRS-Aided MEC 211 10.4 Deep Learning Approaches to IRS-Aided MEC 216 10.5 Comparative Evaluation Results 222 10.6 Conclusions 226 11 Interference Nulling Using Reconfigurable Intelligent Surface 229Tao Jiang, Foad Sohrabi, and Wei Yu 11.1 Introduction 229 11.2 System Model 231 11.3 Interference Nulling via RIS 232 11.4 Learning to Minimize Interference 241 11.5 Conclusions 247 12 Blind Beamforming for IRS Without Channel Estimation 251Kaiming Shen and Zhi-Quan Luo 12.1 Introduction 251 12.2 System Model 252 12.3 Random-Max Sampling (RMS) 254 12.4 Conditional Sample Mean (CSM) 255 12.5 Some Comments on CSM 257 12.6 Field Tests 262 12.7 Conclusion 268 13 RIS in Wireless Information and Power Transfer 271Yang Zhao and Bruno Clerckx 13.1 Introduction 271 13.2 RIS-Aided WPT 274 13.3 RIS-Aided WIPT 285 13.4 Conclusion 291 14 Beamforming Design for Self-Sustainable IRS-Assisted MISO Downlink Systems 297Shaokang Hu and Derrick Wing Kwan Ng 14.1 Introduction 297 14.2 System Model 299 14.3 Problem Formulation 303 14.4 Solution 303 14.5 Numerical Results 307 14.6 Summary 311 14.7 Further Extension 311 15 Optical Intelligent Reflecting Surfaces 315Hedieh Ajam and Robert Schober 15.1 Introduction 315 15.2 System and Channel Model 317 15.3 Communication Theoretical Modeling of Optical IRSs 319 15.4 Design of Optical IRSs for FSO Systems 327 15.5 Simulation Results 331 15.6 Future Extension 333 Bibliography 334 Index 335

Read more less

Book SynopsisFederated Learning for Future Intelligent Wireless Networks Explore the concepts, algorithms, and applications underlying federated learning In Federated Learning for Future Intelligent Wireless Networks, a team of distinguished researchers deliver a robust and insightful collection of resources covering the foundational concepts and algorithms powering federated learning, as well as explanations of how they can be used in wireless communication systems. The editors have included works that examine how communication resource provision affects federated learning performance, accuracy, convergence, scalability, and security and privacy. Readers will explore a wide range of topics that show how federated learning algorithms, concepts, and design and optimization issues apply to wireless communications. Readers will also find: A thorough introduction to the fundamental concepts and algorithms of federated learning, including horizontal, vertical, and hTable of ContentsAbout the Editors xv Preface xvii 1 Federated Learning with Unreliable Transmission in Mobile Edge Computing Systems 1Chenyuan Feng, Daquan Feng, Zhongyuan Zhao, Howard H. Yang, and Tony Q. S. Quek 1.1 System Model 1 1.2 Problem Formulation 4 1.3 A Joint Optimization Algorithm 10 1.4 Simulation and Experiment Results 16 2 Federated Learning with non-IID data in Mobile Edge Computing Systems 23Chenyuan Feng, Daquan Feng, Zhongyuan Zhao, Geyong Min, and Hancong Duan 2.1 System Model 23 2.2 Performance Analysis and Averaging Design 24 2.3 Data Sharing Scheme 30 2.4 Simulation Results 42 3 How Many Resources Are Needed to Support Wireless Edge Networks 49Yi-Jing Liu, Gang Feng, Yao Sun, and Shuang Qin 3.1 Introduction 49 3.2 System Model 50 3.3 Wireless Bandwidth and Computing Resources Consumed for Supporting FL-EnabledWireless Edge Networks 54 3.4 The Relationship between FL Performance and Consumed Resources 59 3.5 Discussions of Three Cases 62 3.6 Numerical Results and Discussion 67 3.7 Conclusion 75 3.8 Proof of Corollary 3.2 76 3.9 Proof of Corollary 3.3 77 4 Device Association Based on Federated Deep Reinforcement Learning for Radio Access Network Slicing 85Yi-Jing Liu, Gang Feng, Yao Sun, and Shuang Qin 4.1 Introduction 85 4.2 System Model 87 4.3 Problem Formulation 90 4.4 Hybrid Federated Deep Reinforcement Learning for Device Association 94 4.5 Numerical Results 103 4.6 Conclusion 109 5 Deep Federated Learning Based on Knowledge Distillation and Differential Privacy 113Hui Lin, Feng Yu, and Xiaoding Wang 5.1 Introduction 113 5.2 RelatedWork 115 5.3 System Model 118 5.4 The Implementation Details of the Proposed Strategy 119 5.5 Performance Evaluation 120 5.6 Conclusions 122 6 Federated Learning-Based Beam Management in Dense Millimeter Wave Communication Systems 127Qing Xue and Liu Yang 6.1 Introduction 127 6.2 System Model 130 6.3 Problem Formulation and Analysis 133 6.4 FL-Based Beam Management in UDmmN 135 6.6 Conclusions 150 7 Blockchain-Empowered Federated Learning Approach for An Intelligent and Reliable D2D Caching Scheme 155Runze Cheng, Yao Sun, Yijing Liu, Le Xia, Daquan Feng, and Muhammad Imran 7.1 Introduction 155 7.2 RelatedWork 157 7.3 System Model 159 7.4 Problem Formulation and DRL-Based Model Training 160 7.5 Privacy-Preserved and Secure BDRFL Caching Scheme Design 165 7.6 Consensus Mechanism and Federated Learning Model Update 170 7.7 Simulation Results and Discussions 173 7.8 Conclusion 177 8 Heterogeneity-Aware Dynamic Scheduling for Federated Edge Learning 181Kun Guo, Zihan Chen, Howard H. Yang, and Tony Q. S. Quek 8.1 Introduction 181 8.2 RelatedWorks 184 8.3 System Model for FEEL 185 8.4 Heterogeneity-Aware Dynamic Scheduling Problem Formulation 189 8.5 Dynamic Scheduling Algorithm Design and Analysis 192 8.6 Evaluation Results 197 8.7 Conclusions 208 8.A.1 Proof of Theorem 8.2 208 8.A.2 Proof of Theorem 8.3 209 9 Robust Federated Learning with Real-World Noisy Data 215Jingyi Xu, Zihan Chen, Tony Q. S. Quek, and Kai Fong Ernest Chong 9.1 Introduction 215 9.2 RelatedWork 217 9.3 FedCorr 219 9.4 Experiments 226 9.5 Further Remarks 232 10 Analog Over-the-Air Federated Learning: Design and Analysis 239Howard H. Yang, Zihan Chen, and Tony Q. S. Quek 10.1 Introduction 239 10.2 System Model 241 10.3 Analog Over-the-Air Model Training 242 10.4 Convergence Analysis 245 10.5 Numerical Results 250 10.6 Conclusion 253 11 Federated Edge Learning for Massive MIMO CSI Feedback 257Shi Jin, Yiming Cui, and Jiajia Guo 11.1 Introduction 257 11.2 System Model 259 11.3 FEEL for DL-Based CSI Feedback 260 11.4 Simulation Results 264 11.5 Conclusion 268 12 User-Centric Decentralized Federated Learning for Autoencoder-Based CSI Feedback 273Shi Jin, Jiajia Guo, Yan Lv, and Yiming Cui 12.1 Autoencoder-Based CSI Feedback 273 12.2 User-Centric Online Training for AE-Based CSI Feedback 275 12.3 Multiuser Online Training Using Decentralized Federated Learning 279 12.4 Numerical Results 283 12.5 Conclusion 287 Bibliography 287 Index 291

Read more less

Book SynopsisJOINT COMMUNICATIONS AND SENSING Authoritative resource systematically introducing JCAS technologies and providing valuable information and knowledge to researchers and engineers Based on over six years of dedicated research on joint communications and sensing (JCAS) by the authors, their collaborators, and students, Joint Communications and Sensing is the first book to comprehensively cover the subject of JCAS, which is expected to deliver huge cost and energy savings, and therefore has become a hallmark of future 6G and next generation radar technologies. The book has three parts. Part I presents the basic JCAS concepts and applications and the basic signal processing algorithms to support JCAS. Part II covers communications-centric JCAS designs that describe how sensing can be integrated into communications networks such as 5G and 6G. Part III presents ways to integrate communications in various radar sensing technologies and platforms.Table of ContentsAcknowledgments xiii Preface xv Acronyms xvii Part I Fundamentals of Joint Communications and Sensing (JCAS) 1 1 Introduction to Joint Communications and Sensing (JCAS) 3 1.1 Background 3 1.2 Three Categories of JCAS Systems 5 1.2.1 Major Differences Between Communications and Sensing 7 1.2.2 Communications-Centric Design 12 1.2.3 Radar-Centric Design 15 1.2.4 Joint Design without an Underlying System 17 1.2.5 Summary of Key Research Problems 18 1.3 Potential Sensing Applications of JCAS 18 1.4 Book Organization 22 References 24 2 Signal Processing Fundamentals for JCAS 31 2.1 Channel Model for Communications and Radar 31 2.2 Basic Communication Signals and Systems 33 2.2.1 Single-Carrier MIMO 33 2.2.2 MIMO-OFDM 34 2.2.3 Transmitter and Receiver Signal Processing in Communications 34 2.3 MIMO Radar Signals and Systems 36 2.3.1 Single-Carrier MIMO Radar 36 2.3.2 MIMO-OFDM Radar 37 2.3.3 FH-MIMO Radar 38 2.4 Basic Signal Processing for Radar Sensing 40 2.4.1 Matched Filtering 40 2.4.2 Moving Target Detection (MTD) 41 2.4.3 Spatial-Domain Processing 42 2.4.4 Target Detection 43 2.4.5 Spatial Refinement 44 2.5 Signal Processing Basics for Communication-Centric JCAS 44 2.5.1 802.11ad JCAS Systems 44 2.5.2 Mobile Network with JCAS Capabilities 46 2.5.3 Sensing Parameter Estimation 46 2.5.3.1 Direct and Indirect Sensing 47 2.5.3.2 Sensing Algorithms 49 2.6 Signal Processing Basics for DFRC 50 2.6.1 Embedding Information in RadarWaveform 50 2.6.2 Signal Reception and Processing for Communications 52 2.6.2.1 Demodulation 53 2.6.2.2 Channel Estimation 54 2.6.3 Codebook Design 54 2.7 Conclusions 55 References 55 3 Efficient Parameter Estimation 59 3.1 Q-Shifted Estimator (QSE) 60 3.2 Refined QSE (QSEr) 62 3.2.1 Impact ofq 62 3.2.2 Refined Optimalq 66 3.2.3 Numerical Illustration of QSEr 67 3.3 Padé approximation-Enabled Estimator 70 3.3.1 Core Updating Function 71 3.3.2 Initialization and Overall Estimation Procedure 74 3.3.3 Numerical Illustrations 76 3.4 Conclusions 80 References 80 Part II Communication-Centric JCAS 83 4 Perceptive Mobile Network (PMN) 85 4.1 Framework for PMN 85 4.1.1 System Platform and Infrastructure 86 Trim Size: 6in x 9in Single Column Wu982913 ftoc.tex V1 - 09/06/2022 5:13pm Page vii [1] [1] [1] [1] Contents vii 4.1.1.1 CRAN 87 4.1.1.2 Standalone BS 87 4.1.2 Three Types of Sensing Operations 88 4.1.2.1 Downlink Active Sensing 88 4.1.2.2 Downlink Passive Sensing 88 4.1.2.3 Uplink Sensing 89 4.1.2.4 Comparison 89 4.1.3 Signals Usable from 5G NR for Radio Sensing 90 4.1.3.1 Reference Signals Used for Channel Estimation 90 4.1.3.2 Nonchannel Estimation Signals 92 4.1.3.3 Data Payload Signals 92 4.2 System Modifications to Enable Sensing 92 4.2.1 Dedicated Transmitter for Uplink Sensing 93 4.2.2 Dedicated Receiver for Downlink (and Uplink) Sensing 94 4.2.3 Full-Duplex Radios for Downlink Sensing 94 4.2.4 Base Stations with Widely Separated Transmitting and Receiving Antennas 96 4.3 System Issues 98 4.3.1 Performance Bounds 98 4.3.2 Waveform Optimization 100 4.3.2.1 Spatial Optimization 102 4.3.2.2 Optimization in Time and Frequency Domains 105 4.3.2.3 Optimization with Next-Generation Signaling Formats 106 4.3.3 Antenna Array Design 106 4.3.3.1 Virtual MIMO and Antenna Grouping 107 4.3.3.2 Sparse Array Design 108 4.3.3.3 Spatial Modulation 109 4.3.3.4 Reconfigurable Intelligent Surface-Assisted JCAS 109 4.3.4 Clutter Suppression Techniques 110 4.3.4.1 Recursive Moving Averaging (RMA) 112 4.3.4.2 Gaussian Mixture Model (GMM) 113 4.3.5 Sensing Parameter Estimation 114 4.3.5.1 Periodogram such as 2D DFT 115 4.3.5.2 Subspace-Based Spectrum Analysis Techniques 115 4.3.5.3 On-Grid Compressive Sensing Algorithms 117 4.3.6 Resolution of Sensing Ambiguity 119 4.3.7 Pattern Analysis 122 4.3.8 Networked Sensing under Cellular Topology 123 4.3.8.1 Fundamental Theories and Performance Bounds for “Cellular Sensing Networks” 123 4.3.8.2 Distributed Sensing with Node Grouping and Cooperation 124 4.3.9 Sensing-Assisted Communications 124 4.3.9.1 Sensing-Assisted Beamforming 124 4.3.9.2 Sensing-Assisted Secure Communications 128 4.4 Conclusions 128 References 128 5 Integrating Low-Complexity and Flexible Sensing into Communication Systems: A Unified Sensing Framework 139 5.1 Problem Statement and Signal Model 139 5.1.1 Signal Model 140 5.1.2 Classical OFDM Sensing (COS) 142 5.1.3 Problem Statement 143 5.1.3.1 CP-limited Sensing Distance 143 5.1.3.2 Communication-limited Velocity measurement 143 5.1.3.3 COS adapted for DFT-S-OFDM 144 5.2 A Low-Complexity Sensing Framework 144 5.3 Performance Analysis 150 5.3.1 Preliminary Results 150 5.3.2 Analyzing Signal Components in Two RDMs 151 5.3.3 Comparison and Insights 154 5.3.4 Criteria for Setting Key Sensing Parameters 157 5.4 Simulation Results 158 5.4.1 Illustrating SINRs in RDMs 159 5.4.2 Illustration of Target Detection 162 5.5 Conclusions 166 References 167 6 Sensing Framework Optimization 169 6.1 Echo Preprocessing 169 6.1.1 Reshaping 170 6.1.2 Virtual Cyclic Prefix (VCP) 171 6.1.3 Removing Communication Information 174 6.2 Target Parameter Estimation 177 6.2.1 Parameter Estimation Method 177 6.2.2 Computational Complexity 181 6.3 Optimizing Parameters of Sensing Methods 182 6.3.1 Preliminary Results 183 6.3.2 Maximizing SINR for Parameter Estimation 184 6.4 Simulation Results 186 6.4.1 Comparison with Benchmark Method 186 Trim Size: 6in x 9in Single Column Wu982913 ftoc.tex V1 - 09/06/2022 5:13pm Page ix [1] [1] [1] [1] Contents ix 6.4.2 Wide Applicability 189 6.5 Conclusions 192 References 193 Part III Radar-Centric Joint Communications and Sensing 195 7 FH-MIMO Dual-Function Radar-Based Communications: Single-Antenna Receiver 197 7.1 Problem Statement 198 7.2 Waveform Design for FH-MIMO DFRC 199 7.2.1 FH-MIMO RadarWaveform 200 7.2.2 Overall Channel Estimation Scheme 202 7.2.2.1 Estimate Timing Offset 203 7.2.2.2 Estimate Channel Parameters 203 7.3 Estimating Timing Offset 203 7.3.1 Two Estimation Methods 204 7.3.2 Performance Analysis and Comparison of the Estimators 205 7.3.3 Design of a Suboptimal Hopping Frequency Sequence 208 7.4 Estimating Channel Response 209 7.4.1 Estimation Method 209 7.4.2 Complexity Analysis 210 7.5 Using Estimations in Data Communications 211 7.6 Extensions to Multipath Cases 212 7.7 Simulation Results 214 7.8 Conclusions 219 References 219 8 Frequency-Hopping MIMO Radar-Based Communications with Multiantenna Receiver 221 8.1 Signal Model 221 8.2 The DFRC Signal Mode 223 8.3 A Multiantenna Receiving Scheme 226 8.3.1 Estimating Channel Response 226 8.3.2 Estimating Timing Offset 227 8.3.2.1 Estimating L𝜂 228 8.3.2.2 Removing Estimation Ambiguity 229 8.3.3 Information Demodulation 230 8.3.3.1 Estimating khm 230 8.3.3.2 FHCS Demodulation 232 8.3.3.3 PSK Demodulation 232 8.4 Performance Analysis 232 8.4.1 Performance of Channel Coefficient Estimation 232 8.4.2 Performance of Timing Offset Estimation 233 8.4.3 Communication Performance 234 8.4.3.1 Achievable Rate 234 8.4.3.2 SER of PSK-Based FH-MIMO DFRC 234 8.5 Simulations 235 8.6 Conclusions 240 References 240 9 Integrating Secure Communications into Frequency Hopping MIMO Radar with Improved Data Rates 243 9.1 Signal Models and Overall Design 243 9.1.1 Signal Model of Bob 244 9.1.2 Signal Model of Eve 245 9.1.3 Overall Description 246 9.1.4 Maximum Achievable Rate (MAR) 247 9.2 Elementwise Phase Compensation 249 9.2.1 AoD-Dependence Issue of Hopping Frequency Permutation Selection (HFPS) Demodulation 249 9.2.2 Elementwise phase compensation and HFPS Demodulation at Bob 250 9.2.3 Enhancing Physical-Layer Security by Elementwise Phase Compensation 252 9.3 Random Sign Reversal 253 9.3.1 Random Sign Reversal and Maximum Likelihood (ML) Decoding 253 9.3.2 Detecting Random Sign Reversal at Bob 254 9.3.3 Random Sign Reversal Impact Analysis 255 9.3.4 Impact of Presented Design on Radar Performance 258 9.3.4.1 Impact of HFCS on R(𝜏) 258 9.3.4.2 Impact of HFPS on R(𝜏) 259 9.3.4.3 Impact of Elementwise Phase Compensation and Random Sign Reversal on R(𝜏) 259 9.3.4.4 Limitations of Presented Design for Radar Applications 260 9.3.5 Extension to Multipath and Multiuser Scenarios 260 9.3.5.1 Multipath Scenario 260 9.3.5.2 Multiuser Scenario 261 9.4 Simulation Results 261 9.5 Conclusions 267 References 267 Trim Size: 6in x 9in Single Column Wu982913 ftoc.tex V1 - 09/06/2022 5:13pm Page xi [1] [1] [1] [1] Contents xi A Proofs, Analyses, and Derivations 271 A.1 Proof of Lemma 5.1 271 A.2 Proof of Lemma 5.2 271 A.3 Proof of Lemma 5.3 272 A.4 Proof of Proposition 5.1 273 A.5 Proof of Proposition 5.2 274 A.6 Proof of Proposition 6.1 275 A.7 Deriving the Powers of the Four Terms of X̃ n[l] Given in (6.33) 277 A.8 Proof of Proposition 6.2 280 A.9 Proof of Proposition 6.3 281 A.10 Deriving (9.31) 282 References 283 Index 285

Read more less

Book SynopsisMobility Models for Next Generation Wireless Networks: Ad Hoc, Vehicular and Mesh Networks provides the reader with an overview of mobility modelling, encompassing both theoretical and practical aspects related to the challenging mobility modelling task.Table of ContentsList of Figures xv List of Tables xxiii About the Author xxv Preface xxvii Acknowledgments xxxiii List of Abbreviations xxxv Part I INTRODUCTION 1 Next Generation Wireless Networks 3 1.1 WLAN and Mesh Networks 5 1.2 Ad Hoc Networks 8 1.3 Vehicular Networks 10 1.4 Wireless Sensor Networks 13 1.5 Opportunistic Networks 14 2 Modeling Next Generation Wireless Networks 19 2.1 Radio Channel Models 20 2.2 The Communication Graph 26 2.3 The Energy Model 31 3 Mobility Models for Next Generation Wireless Networks 33 3.1 Motivation 33 3.2 Cellular vs. Next Generation Wireless Network Mobility Models 35 3.3 A Taxonomy of Existing Mobility Models 38 3.4 Mobility Models and Real-World Traces: The CRAWDAD Resource 43 3.5 Basic Definitions 45 Part II “GENERAL-PURPOSE” MOBILITY MODELS 4 Random Walk Models 51 4.1 Discrete Random Walks 52 4.2 Continuous Random Walks 55 4.3 Other Random Walk Models 57 4.4 Theoretical Properties of Random Walk Models 58 5 The Random Waypoint Model 61 5.1 The RWP Model 62 5.2 The Node Spatial Distribution of the RWP Model 64 5.3 The Average Nodal Speed of the RWP Model 69 5.4 Variants of the RWP Model 73 6 Group Mobility and Other Synthetic Mobility Models 75 6.1 The RPGM Model 76 6.2 Other Synthetic Mobility Models 83 7 Random Trip Models 89 7.1 The Class of Random Trip Models 89 7.2 Stationarity of Random Trip Models 93 7.3 Examples of Random Trip Models 94 Part III MOBILITY MODELS FOR WLAN AND MESH NETWORKS 8 WLAN and Mesh Networks 101 8.1 WLAN and Mesh Networks: State of the Art 101 8.2 WLAN and Mesh Networks: User Scenarios 107 8.3 WLAN and Mesh Networks: Perspectives 109 8.4 Further Reading 111 9 Real-World WLAN Mobility 113 9.1 Real-World WLAN Traces 113 9.2 Features of WLAN Mobility 116 10 WLAN Mobility Models 121 10.1 The LH Mobility Model 122 10.2 The KKK Mobility Model 129 10.3 Final Considerations and Further Reading 137 Part IV MOBILITY MODELS FOR VEHICULAR NETWORKS 11 Vehicular Networks 141 11.1 Vehicular Networks: State of the Art 141 11.2 Vehicular Networks: User Scenarios 146 11.3 Vehicular Networks: Perspectives 150 11.4 Further Reading 151 12 Vehicular Networks: Macroscopic and Microscopic Mobility Models 153 12.1 Vehicular Mobility Models: The Macroscopic View 154 12.2 Vehicular Mobility Models: The Microscopic View 156 12.3 Further Reading 157 13 Microscopic Vehicular Mobility Models 159 13.1 Simple Microscopic Mobility Models 159 13.2 The SUMO Mobility Model 164 13.3 Integrating Vehicular Mobility and Wireless Network Simulation 168 Part V MOBILITY MODELS FOR WIRELESS SENSOR NETWORKS 14 Wireless Sensor Networks 175 14.1 Wireless Sensor Networks: State of the Art 175 14.2 Wireless Sensor Networks: User Scenarios 180 14.3 WSNs: Perspectives 183 14.4 Further Reading 184 15 Wireless Sensor Networks: Passive Mobility Models 185 15.1 Passive Mobility in WSNs 186 15.2 Mobility Models for Wildlife Tracking Applications 187 15.3 Modeling Movement Caused by External Forces 191 16 Wireless Sensor Networks: Active Mobility Models 197 16.1 Active Mobility of Sensor Nodes 198 16.2 Active Mobility of Sink Nodes 208 Part VI MOBILITY MODELS FOR OPPORTUNISTIC NETWORKS 17 Opportunistic Networks 217 17.1 Opportunistic Networks: State of the Art 217 17.2 Opportunistic Networks: User Scenarios 219 17.3 Opportunistic Networks: Perspectives 222 17.4 Further Reading 223 18 Routing in Opportunistic Networks 225 18.1 Mobility-Assisted Routing in Opportunistic Networks 225 18.2 Opportunistic Network Mobility Metrics 231 19 Mobile Social Network Analysis 237 19.1 The Social Network Graph 238 19.2 Centrality and Clustering Metrics 239 19.3 Characterizations of Human Mobility 244 19.4 Further Reading 250 20 Social-Based Mobility Models 251 20.1 The Weighted Random Waypoint Mobility Model 252 20.2 The Time-Variant Community Mobility Model 254 20.3 The Community-Based Mobility Model 256 20.4 The SWIM Mobility Model 259 20.5 The Self-Similar Least Action Walk Model 264 20.6 The Home-MEG Model 267 20.7 Further Reading 270 Part VII CASE STUDIES 21 Random Waypoint Model and Wireless Network Simulation 275 21.1 RWP Model and Simulation Accuracy 276 21.2 Removing the Border Effect 278 21.3 Removing Speed Decay 285 21.4 The RWP Model and “Perfect Simulation” 287 22 Mobility Modeling and Opportunistic Network Performance Analysis 293 22.1 Unicast in Opportunistic Networks 293 22.2 Broadcast in Opportunistic Networks 299 Appendix A Elements of Probability Theory 309 A.1 Basic Notions of Probability Theory 309 A.2 Probability Distributions 313 A.3 Markov Chains 317 Appendix B Elements of Graph Theory, Asymptotic Notation, and Miscellaneous Notions 323 B.1 Asymptotic Notation 323 B.2 Elements of Graph Theory 326 B.3 Miscellaneous Notions 330 References 333 Index 335

Read more less

Book SynopsisMIMO systems have been known to better the quality of service for wireless communication systems. This book discusses emerging techniques in MIMO systems to reduce complexities and keep benefits unaffected at the same time. It discusses about benefits and shortcomings of various MIMO technologies like spatial multiplexing, space time coding, spatial modulation, transmit antenna selection and various power allocation schemes to optimize the performance. Crux of the book is focus on MIMO communication over generalized fading channels as they can model the propagation of signals in a non-homogeneous environment. Relevant MATLAB codes are also included in the appendices. Book is aimed at graduate students and researchers in electronics and wireless engineering specifically interested in electromagnetic theory, antennas and propagation, future wireless systems, signal processing.Table of Contents1. Introduction to MIMO Systems. 2. Generalized Fading Channels. 3. Spatial Multiplexing. 4. Spatial Modulation. 5. Transmit Antenna Selection. 6. Space Time Block Coded MIMO Systems. 7. MIMO for 5G Mobile Communications. A. Appendix. B. MATLAB codes for generating results.

Read more less

Book SynopsisAn undeniably rich and thorough guide to satellite communication engineering, Satellite Communication Engineering, Second Edition presents the fundamentals of information communications systems in a simple and succinct way. This book considers both the engineering aspects of satellite systems as well as the practical issues in the broad field of information transmission. Implementing concepts developed on an intuitive, physical basis and utilizing a combination of applications and performance curves, this book starts off with a progressive foundation in satellite technology, and then moves on to more complex concepts with ease.What's New in the Second Edition:The second edition covers satellite and Earth station design; global positioning systems; antenna tracking; links and communications systems; error detection and correction; data security; regulations and procedures for system modeling; integration; testing; and reliability and perfoTrade Review"It's application is industry based. …it will excite readers especially with it empirical examples."––Kayode Odimayomi, METI-University of Port Harcourt, Nigeria"The book provides a simple explanation of the very technical aspects of satellite systems engineering. It covers a wide range of topics and includes useful topics of Design of Satellite Links, Satellite Communication Network Access Types and Error Detection and Correction Coding Schemes, Regulatory Agencies and Procedures and Mobile Satellite Systems, which is a recent phenomenon. Very good examples are used to illustrate the design procedures."—Tokunbo Ogunfunmi, Santa Clara universityTable of ContentsBasic Principles of Satellite Communications. Satellites. Earth Stations. Satellite Links. Communication Networks and Systems. Error Detection and Correction for Coding Schemes. Regulatory Agencies and Procedures. Mobile Satellite System Services. Appendices. Index.

Read more less

Book SynopsisDelay- and Disruption Tolerant Networks (DTNs) are networks subject to arbitrarily long-lived disruptions in connectivity and therefore cannot guarantee end-to-end connectivity at all times. Consequently DTNs called for novel core networking protocols since most existing Internet protocols rely on the network's ability to maintain end-to-end communication between participating nodes. This book presents the fundamental principles that underline DTNs. It explains the state-of-the-art on DTNs, their architecture, protocols, and applications. It also explores DTN's future technological trends and applications. Its main goal is to serve as a reference for researchers and practitioners.Table of Contents1. Introduction, Daniel Oberhaus.2. Delay and Disruption Tolerant Network Architecture, Aloizio P. Silva, Scott Burleigh, and Katia Obraczka.3. DTN Platforms, Aloizio P. Silva and Scott Burleigh.4. Case Study: Interplanetary Networks, Aloizio P. Silva and Scott Burleigh5. Delay and Disruption Tolerant Network Routing, Aloizio P. Silva, Scott Burleigh, and Katia Obraczka6. DTN Coding, Marius Feldmann, Felix Walter, Tomaso de Cola, and Gianluigi Liva.7. DTN for Spacecraft, Keith Scott.8. Delay-Tolerant Security, Edward Birrane.9. DTN of Things, Juan A. Fraire and Jorge M. Finochietto.10. DTN Congestion Control, Aloizio P. Silva, Scott Burleigh, and Katia Obraczka. 11. Licklider Transmission Protocol (LTP), Nicholas Ansell. 12. Delay-/Disruption- Tolerant Networking Performance Evaluation with DTNperf_3, Carlo Caini.

Read more less

Book SynopsisThis fourth edition of the text reflects the continuing increase in awareness and use of computational electromagnetics and incorporates advances and refinements made in recent years. Most notable among these are the improvements made to the standard algorithm for the finite-difference time-domain (FDTD) method and treatment of absorbing boundary conditions in FDTD, finite element, and transmission-line-matrix methods. It teaches the readers how to pose, numerically analyze, and solve EM problems, to give them the ability to expand their problem-solving skills using a variety of methods, and to prepare them for research in electromagnetism. Includes new homework problems in each chapter. Each chapter is updated with the current trends in CEM. Adds a new appendix on CEM codes, which covers commercial and free codes. Provides updated MATLAB code. Table of Contents1. Fundamental Concepts 2. Analytical Methods 3. Finite Difference Methods 4. Variational Methods 5. Moment Methods 6. Finite Element Method 7. Transmission-Line-Matrix Method 8. Monte Carlo Methods 9. Method of Lines

Read more less

Book SynopsisThe book addresses the need to investigate new approaches to lower energy requirement in multiple application areas and serves as a guide into emerging circuit technologies. It explores revolutionary device concepts, sensors, and associated circuits and architectures that will greatly extend the practical engineering limits of energy-efficient computation. The book responds to the need to develop disruptive new system architecutres, circuit microarchitectures, and attendant device and interconnect technology aimed at achieving the highest level of computational energy efficiency for general purpose computing systems.Features Discusses unique technologies and material only available in specialized journal and conferences Covers emerging applications areas, such as ultra low power communications, emerging bio-electronics, and operation in extreme environments Explores broad circuit operation, ex. analog, RF, memory, and digital circuits ContaiTable of Contents1. Clock Generation and Distribution for Low-Power Digital Systems. 2. Design of Low Standby Power Fully Integrated Voltage Regulators. 3. On-Chip Regulators for Low Voltage and Portable Systems-on-Chip. 4. Low-Power Biosensor Design Techniques Based on Information theoretic Principles. 5. A Cost-Effective TAF-DPS Syntonuzation Scheme of Improving Clock Frequency Accuracy and Long-Term Frequency Stability for Universal Applications. 6. Exploiting Time: The Intersection Point of Multidiciplines and the Nest Challenge and Opportunity in the Making of Electronics. 7. Aging Evaluation and Mitigation Techniques Targeting FPGA Devices.

Read more less

Book Synopsis

Read more less

Book SynopsisIn the twenty-first century city, wireless waves constitute an imperceptible, immersive, all-encompassing environment. Nowhere is this more so than in China, where a hyperdense network of mobile media has restructured daily life. Anna Greenspan re-imagines the relationship between China and wirelessness by synthesizing contemporary media theory with modern Chinese thought. It focuses specifically on the work of three critical figures: Tan Sitong ??? (1865?1898), Xiong Shili ??? (1885?1968) and Mou Zongsan ??? (1909?1995).

Read more less

Book SynopsisA Complete Reference for the 21st Century Until recently, much of the communications technology in the former Eastern bloc countries was largely unknown. Due to the historically competitive nature of East/West relations, scientific groups operated independently, without the benefit of open communication on theoretical frameworks and experimental technologies. As these countries have begun to bridge the gap and work in a more cooperative environment, the need has grown for a comprehensive guide which assimilates all the information in this vast knowledge bank. Ionosphere and Applied Aspects of Radio Communication and Radar meets the demand for an updated reference on this continually evolving global technology. This book examines the changes that have occurred in the past two or three decades. It thoroughly reviews ionospheric radio propagation, over-horizon and above-horizon radars, and miniature ionospheric stations used for investigating nonregulaTable of ContentsThe Regular Ionosphere: Main Characteristics and Processes. Nonlinear Phenomena and Plasma Instabilities in the Disturbed Irregluar Ionosphere. Radio Signal Presentation in the Ionospheric Communication Channel. Fading Phenomena in Ionospheric Communications Channels. Evolution of Plasma Irregularities in the Ionosphere. Modern Radiophysical Methods of Investigation of Ionospheric Irregularities. Performance of Radio Communications in Ionospheric Channels. Optical and Radio Systems for Investigation of the Ionosphere and Ionospheric Communication Channels. Performance of Land-Satellite Communication Links Passing through the Irregular Ionosphere

Read more less