Description

Book Synopsis
INTELLIGENT 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 d

Table of Contents

About the Editors xiii

List of Contributors xv

Preface xxi

Acknowledgement xxiii

Part I Fundamentals of IRS 1

1 Introduction to Intelligent Surfaces 3
Kaitao 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 15
Zijian 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 59
Kaitao 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 85
Ruiqi (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 117
Stefano 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 139
George 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 167
Boyu 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 187
Ximing 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 207
Xiaoyan 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 229
Tao 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 251
Kaiming 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 271
Yang 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 297
Shaokang 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 315
Hedieh 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

Intelligent Surfaces Empowered 6g Wireless

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    A Hardback by Wu, Trung Q. Duong, Derrick Wing Kwan Ng

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      View other formats and editions of Intelligent Surfaces Empowered 6g Wireless by Wu

      Publisher: John Wiley & Sons Inc
      Publication Date: 12/1/2023 12:00:00 AM
      ISBN13: 9781119913092, 978-1119913092
      ISBN10: 1119913098

      Description

      Book Synopsis
      INTELLIGENT 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 d

      Table of Contents

      About the Editors xiii

      List of Contributors xv

      Preface xxi

      Acknowledgement xxiii

      Part I Fundamentals of IRS 1

      1 Introduction to Intelligent Surfaces 3
      Kaitao 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 15
      Zijian 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 59
      Kaitao 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 85
      Ruiqi (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 117
      Stefano 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 139
      George 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 167
      Boyu 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 187
      Ximing 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 207
      Xiaoyan 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 229
      Tao 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 251
      Kaiming 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 271
      Yang 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 297
      Shaokang 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 315
      Hedieh 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

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