John Wiley & Sons Next Generation Multiple Access Cover Highly comprehensive resource investigating how next-generation multiple access (NGMA) relates to un.. Product #: 978-1-394-18049-3 Regular price: $126.17 $126.17 Auf Lager

Next Generation Multiple Access

Liu, Yuanwei / Liu, Liang / Ding, Zhiguo / Shen, Xuemin (Herausgeber)

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1. Auflage Januar 2024
624 Seiten, Hardcover
Wiley & Sons Ltd

ISBN: 978-1-394-18049-3
John Wiley & Sons

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Highly comprehensive resource investigating how next-generation multiple access (NGMA) relates to unrestricted global connection, business requirements, and sustainable wireless networks

Next Generation Multiple Access is a comprehensive, state-of-the-art, and approachable guide to the fundamentals and applications of next-generation multiple access (NGMA) schemes, guiding the future development of industries, government requirements, and military utilization of multiple access systems for wireless communication systems and providing various application scenarios to fit practical case studies.

The scope and depth of this book are balanced for both beginners to advanced users. Additional references are provided for readers who wish to learn more details about certain subjects. Applications of NGMA outside of communications, including data and computing assisted by machine learning, protocol designs, and others, are also covered.

Written by four leading experts in the field, Next Generation Multiple Access includes information on:
* Foundation and application scenarios for non-orthogonal multiple access (NOMA) systems, including modulation, detection, power allocation, and resource management
* NOMA's interaction with alternate applications such as satellite communication systems, terrestrial-satellite communication systems, and integrated sensing
* Collision resolution, compressed sensing aided massive access, latency management, deep learning enabled massive access, and energy harvesting
* Holographic-pattern division multiple access, over-the-air transmission, multi-dimensional multiple access, sparse signal detection, and federated meta-learning assisted resource management

Next Generation Multiple Access is an essential reference for those who are interested in discovering practical solutions using NGMA technology, including researchers, engineers, and graduate students in the disciplines of information engineering, telecommunications engineering, and computer engineering.

About the Editors xix

List of Contributors xxiii

Preface xxxiii

Acknowledgments xxxv

1 Next Generation Multiple Access Toward 6G 1
Yuanwei Liu, Liang Liu, Zhiguo Ding, and Xuemin Shen

1.1 The Road to NGMA 1

1.2 Non-Orthogonal Multiple Access 3

1.3 Massive Access 4

1.4 Book Outline 5

Part I Evolution of NOMA Towards NGMA 9

2 Modulation Techniques for NGMA/NOMA 11
Xuan Chen, Qiang Li, and Miaowen Wen

2.1 Introduction 11

2.2 Space-Domain IM for NGMA 12

2.3 Frequency-Domain IM for NGMA 22

2.4 Code-Domain IM for NGMA 31

2.5 Power-Domain IM for NGMA 35

2.6 Summary 43

3 NOMA Transmission Design with Practical Modulations 47
Tianying Zhong, Yuan Wang, and Jiaheng Wang

3.1 Introduction 47

3.2 Fundamentals 49

3.3 Effective Throughput Analysis 53

3.4 NOMA Transmission Design 56

3.5 Numerical Results 65

3.6 Conclusion 68

4 Optimal Resource Allocation for NGMA 71
Sepehr Rezvani and Eduard Jorswieck

4.1 Introduction 71

4.2 Single-Cell Single-Carrier NOMA 73

4.3 Single-Cell Multicarrier NOMA 80

4.4 Multi-cell NOMA with Single-Cell Processing 84

4.5 Numerical Results 93

4.6 Conclusions 96

5 Cooperative NOMA 101
Yao Xu, Bo Li, Nan Zhao, Jie Tang, Dusit Niyato, and Kai-Kit Wong

5.1 Introduction 101

5.2 System Model for D2MD-CNOMA 102

5.3 Adaptive Aggregate Transmission 103

5.4 Performance Analysis 107

5.5 Numerical Results and Discussion 117

6 Multi-scale-NOMA: An Effective Support to Future Communication-Positioning Integration System 127
Lu Yin, Wenfang Guo, and Tianzhu Song

6.1 Introduction 127

6.2 Positioning in Cellular Networks 128

6.3 MS-NOMA Architecture 130

6.4 Interference Analysis 131

6.5 Resource Allocation 139

6.6 Performance Evaluation 145

7 NOMA-Aware Wireless Content Caching Networks 161
Yaru Fu, Zheng Shi, and Tony Q. S. Quek

7.1 Introduction 161

7.2 System Model 164

7.3 Algorithm Design 169

7.4 Numerical Simulation 173

7.5 Conclusion 178

8 NOMA Empowered Multi-Access Edge Computing and Edge Intelligence 181
Yuan Wu, Yang Li, Liping Qian, and Xuemin Shen

8.1 Introduction 181

8.2 Literature Review 183

8.3 System Model and Formulation 185

8.4 Algorithms for Optimal Offloading 189

8.5 Numerical Results 194

8.6 Conclusion 197

9 Exploiting Non-orthogonal Multiple Access in Integrated Sensing and Communications 205
Xidong Mu, Zhaolin Wang, and Yuanwei Liu

9.1 Introduction 205

9.2 Developing Trends and Fundamental Models of ISAC 206

9.3 Novel NOMA Designs in Downlink and Uplink ISAC 209

9.4 Case Study: System Model and Problem Formulation 213

9.5 Case Study: Proposed Solutions 216

9.6 Case Study: Numerical Results 219

9.7 Conclusions 223

Part II Massive Access for NGMA 227

10 Capacity of Many-Access Channels 229
Lina Liu and Dongning Guo

10.1 Introduction 229

10.2 The Many-Access Channel Model 231

10.3 Capacity of the MnAC 232

10.4 Energy Efficiency of the MnAC 240

10.5 Discussion and Open Problems 253

11 Random Access Techniques for Machine-Type Communication 259
Jinho Choi

11.1 Fundamentals of Random Access 259

11.2 A Game Theoretic View 263

11.3 Random Access Protocols for MTC 266

11.4 Variants of 2-Step Random Access 269

11.5 Application of NOMA to Random Access 273

11.6 Low-Latency Access for MTC 279

12 Grant-Free Random Access via Compressed Sensing: Algorithm and Performance 287
Yongpeng Wu, Xinyu Xie, Tianya Li, and Boxiao Shen

12.1 Introduction 287

12.2 Joint Device Detection, Channel Estimation, and Data Decoding with Collision Resolution for MIMO Massive Unsourced Random Access 288

12.3 Exploiting Angular Domain Sparsity for Grant-Free Random Access: A Hybrid AMP Approach 294

12.4 LEO Satellite-Enabled Grant-Free Random Access 301

12.5 Concluding Remarks 311

13 Algorithm Unrolling for Massive Connectivity in IoT Networks 315
Yinan Zou, Yong Zhou, and Yuanming Shi

13.1 Introduction 315

13.2 System Model 317

13.3 Learned Iterative Shrinkage Thresholding Algorithm for Massive Connectivity 319

13.4 Learned Proximal Operator Methods for Massive Connectivity 324

13.5 Training and Testing Strategies 327

13.6 Simulation Results 328

13.7 Conclusions 331

14 Grant-Free Massive Random Access: Joint Activity Detection, Channel Estimation, and Data Decoding 335
Xinyu Bian, Yuyi Mao, and Jun Zhang

14.1 Introduction 335

14.2 System Model 337

14.3 Joint Estimation via a Turbo Receiver 339

14.4 A Low-Complexity Side Information-Aided Receiver 349

14.5 Simulation Results 353

14.6 Summary 358

15 Joint User Activity Detection, Channel Estimation, and Signal Detection for Grant-Free Massive Connectivity 361
Zhichao Shao, Shuchao Jiang, Chongbin Xu, Xiaojun Yuan, and Xin Wang

15.1 Introduction 361

15.2 Receiver Design for Synchronous Massive Connectivity 363

15.3 Receiver Design for Asynchronous Massive Connectivity 372

15.4 Conclusion 387

16 Grant-Free Random Access via Covariance-Based Approach 391
Ya-Feng Liu, Wei Yu, Ziyue Wang, Zhilin Chen, and Foad Sohrabi

16.1 Introduction 391

16.2 Device Activity Detection in Single-Cell Massive MIMO 393

16.3 Device Activity Detection in Multi-Cell Massive MIMO 402

16.4 Practical Issues and Extensions 409

16.5 Conclusions 411

17 Deep Learning-Enabled Massive Access 415
Ying Cui, Bowen Tan, Wang Liu, and Wuyang Jiang

17.1 Introduction 415

17.2 System Model 419

17.3 Model-Driven Channel Estimation 420

17.4 Model-Driven Activity Detection 424

17.5 Auto-Encoder-Based Pilot Design 429

17.6 Numerical Results 431

17.7 Conclusion 438

18 Massive Unsourced Random Access 443
Volodymyr Shyianov, Faouzi Bellili, Amine Mezghani, and Ekram Hossain

18.1 Introduction 443

18.2 URA with Single-Antenna Base Station 444

18.3 URA with Multi-Antenna Base Station 454

Part III Other Advanced Emerging MA Techniques for NGMA 465

19 Holographic-Pattern Division Multiple Access 467
Ruoqi Deng, Boya Di, and Lingyang Song

19.1 Overview of HDMA 469

19.2 System Model 474

19.3 Multiuser Holographic Beamforming 476

19.4 Holographic Pattern Design 479

19.5 Performance Analysis and Evaluation 485

19.6 Summary 490

20 Over-the-Air Computation 495
Yilong Chen, Xiaowen Cao, Jie Xu, Guangxu Zhu, Kaibin Huang, and Shuguang Cui

20.1 Introduction 495

20.2 AirComp Fundamentals 497

20.3 Power Control for AirComp 499

20.4 Beamforming for AirComp 509

20.5 Extension 514

20.6 Conclusion 516

21 Multi-Dimensional Multiple Access for 6G: Efficient Radio Resource Utilization and Value-Oriented Service Provisioning 519
Wudan Han, Jie Mei, and Xianbin Wang

21.1 Introduction 519

21.2 Principle of MDMA 523

21.3 Value-Oriented Operation of MDMA 528

21.4 Multi-Dimensional Resource Utilization in Value-Oriented MDMA 533

21.5 Numerical Results and Analysis 538

21.6 Conclusion 543

22 Efficient Federated Meta-Learning Over Multi-Access Wireless Networks 547
Sheng Yue and Ju Ren

22.1 Introduction 547

22.2 Related Work 549

22.3 Preliminaries and Assumptions 551

22.4 Nonuniform Federated Meta-Learning 554

22.5 Federated Meta-Learning Over Wireless Networks 558

22.6 Extension to First-Order Approximations 568

22.7 Simulation 570

22.8 Conclusion 577

References 578

Index 583
Yuanwei Liu, PhD, is a Senior Lecturer (Associate Professor) with the School of Electronic Engineering and Computer Science at Queen Mary University of London, UK.

Liang Liu, PhD, is an Assistant Professor in the Department of Electrical and Electronic Engineering at Hong Kong Polytechnic University.

Zhiguo Ding, PhD, is a Professor in Communications with the Department of Electrical and Electronic Engineering at the University of Manchester, UK.

Xuemin Shen, PhD, is a Professor with the Department of Electrical and Computer Engineering at the University of Waterloo, Canada.

Y. Liu, Queen Mary University of London, UK; L. Liu, Hong Kong Polytechnic University, Hong Kong, China; Z. Ding, University of Manchester, UK; X. Shen, University of Waterloo, Ontario, Canada