Next Generation Multiple Access
Wiley-IEEE Press (Verlag)
978-1-394-18049-3 (ISBN)
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.
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.
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
| Erscheinungsdatum | 12.01.2024 |
|---|---|
| Sprache | englisch |
| Gewicht | 100 g |
| Themenwelt | Technik ► Elektrotechnik / Energietechnik |
| ISBN-10 | 1-394-18049-7 / 1394180497 |
| ISBN-13 | 978-1-394-18049-3 / 9781394180493 |
| Zustand | Neuware |
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