Next Generation Multiple Access

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 xixList of Contributors xxiiiPreface xxxiiiAcknowledgments xxxv1 Next Generation Multiple Access Toward 6G 1Yuanwei Liu, Liang Liu, Zhiguo Ding, and Xuemin Shen1.1 The Road to NGMA 11.2 Non-Orthogonal Multiple Access 31.3 Massive Access 41.4 Book Outline 5Part I Evolution of NOMA Towards NGMA 92 Modulation Techniques for NGMA/NOMA 11Xuan Chen, Qiang Li, and Miaowen Wen2.1 Introduction 112.2 Space-Domain IM for NGMA 122.3 Frequency-Domain IM for NGMA 222.4 Code-Domain IM for NGMA 312.5 Power-Domain IM for NGMA 352.6 Summary 433 NOMA Transmission Design with Practical Modulations 47Tianying Zhong, Yuan Wang, and Jiaheng Wang3.1 Introduction 473.2 Fundamentals 493.3 Effective Throughput Analysis 533.4 NOMA Transmission Design 563.5 Numerical Results 653.6 Conclusion 684 Optimal Resource Allocation for NGMA 71Sepehr Rezvani and Eduard Jorswieck4.1 Introduction 714.2 Single-Cell Single-Carrier NOMA 734.3 Single-Cell Multicarrier NOMA 804.4 Multi-cell NOMA with Single-Cell Processing 844.5 Numerical Results 934.6 Conclusions 965 Cooperative NOMA 101Yao Xu, Bo Li, Nan Zhao, Jie Tang, Dusit Niyato, and Kai-Kit Wong5.1 Introduction 1015.2 System Model for D2MD-CNOMA 1025.3 Adaptive Aggregate Transmission 1035.4 Performance Analysis 1075.5 Numerical Results and Discussion 1176 Multi-scale-NOMA: An Effective Support to Future Communication–Positioning Integration System 127Lu Yin, Wenfang Guo, and Tianzhu Song6.1 Introduction 1276.2 Positioning in Cellular Networks 1286.3 MS-NOMA Architecture 1306.4 Interference Analysis 1316.5 Resource Allocation 1396.6 Performance Evaluation 1457 NOMA-Aware Wireless Content Caching Networks 161Yaru Fu, Zheng Shi, and Tony Q. S. Quek7.1 Introduction 1617.2 System Model 1647.3 Algorithm Design 1697.4 Numerical Simulation 1737.5 Conclusion 1788 NOMA Empowered Multi-Access Edge Computing and Edge Intelligence 181Yuan Wu, Yang Li, Liping Qian, and Xuemin Shen8.1 Introduction 1818.2 Literature Review 1838.3 System Model and Formulation 1858.4 Algorithms for Optimal Offloading 1898.5 Numerical Results 1948.6 Conclusion 1979 Exploiting Non-orthogonal Multiple Access in Integrated Sensing and Communications 205Xidong Mu, Zhaolin Wang, and Yuanwei Liu9.1 Introduction 2059.2 Developing Trends and Fundamental Models of ISAC 2069.3 Novel NOMA Designs in Downlink and Uplink ISAC 2099.4 Case Study: System Model and Problem Formulation 2139.5 Case Study: Proposed Solutions 2169.6 Case Study: Numerical Results 2199.7 Conclusions 223Part II Massive Access for NGMA 22710 Capacity of Many-Access Channels 229Lina Liu and Dongning Guo10.1 Introduction 22910.2 The Many-Access Channel Model 23110.3 Capacity of the MnAC 23210.4 Energy Efficiency of the MnAC 24010.5 Discussion and Open Problems 25311 Random Access Techniques for Machine-Type Communication 259Jinho Choi11.1 Fundamentals of Random Access 25911.2 A Game Theoretic View 26311.3 Random Access Protocols for MTC 26611.4 Variants of 2-Step Random Access 26911.5 Application of NOMA to Random Access 27311.6 Low-Latency Access for MTC 27912 Grant-Free Random Access via Compressed Sensing: Algorithm and Performance 287Yongpeng Wu, Xinyu Xie, Tianya Li, and Boxiao Shen12.1 Introduction 28712.2 Joint Device Detection, Channel Estimation, and Data Decoding with Collision Resolution for MIMO Massive Unsourced Random Access 28812.3 Exploiting Angular Domain Sparsity for Grant-Free Random Access: A Hybrid AMP Approach 29412.4 LEO Satellite-Enabled Grant-Free Random Access 30112.5 Concluding Remarks 31113 Algorithm Unrolling for Massive Connectivity in IoT Networks 315Yinan Zou, Yong Zhou, and Yuanming Shi13.1 Introduction 31513.2 System Model 31713.3 Learned Iterative Shrinkage Thresholding Algorithm for Massive Connectivity 31913.4 Learned Proximal Operator Methods for Massive Connectivity 32413.5 Training and Testing Strategies 32713.6 Simulation Results 32813.7 Conclusions 33114 Grant-Free Massive Random Access: Joint Activity Detection, Channel Estimation, and Data Decoding 335Xinyu Bian, Yuyi Mao, and Jun Zhang14.1 Introduction 33514.2 System Model 33714.3 Joint Estimation via a Turbo Receiver 33914.4 A Low-Complexity Side Information-Aided Receiver 34914.5 Simulation Results 35314.6 Summary 35815 Joint User Activity Detection, Channel Estimation, and Signal Detection for Grant-Free Massive Connectivity 361Zhichao Shao, Shuchao Jiang, Chongbin Xu, Xiaojun Yuan, and Xin Wang15.1 Introduction 36115.2 Receiver Design for Synchronous Massive Connectivity 36315.3 Receiver Design for Asynchronous Massive Connectivity 37215.4 Conclusion 38716 Grant-Free Random Access via Covariance-Based Approach 391Ya-Feng Liu, Wei Yu, Ziyue Wang, Zhilin Chen, and Foad Sohrabi16.1 Introduction 39116.2 Device Activity Detection in Single-Cell Massive MIMO 39316.3 Device Activity Detection in Multi-Cell Massive MIMO 40216.4 Practical Issues and Extensions 40916.5 Conclusions 41117 Deep Learning-Enabled Massive Access 415Ying Cui, Bowen Tan, Wang Liu, and Wuyang Jiang17.1 Introduction 41517.2 System Model 41917.3 Model-Driven Channel Estimation 42017.4 Model-Driven Activity Detection 42417.5 Auto-Encoder-Based Pilot Design 42917.6 Numerical Results 43117.7 Conclusion 43818 Massive Unsourced Random Access 443Volodymyr Shyianov, Faouzi Bellili, Amine Mezghani, and Ekram Hossain18.1 Introduction 44318.2 URA with Single-Antenna Base Station 44418.3 URA with Multi-Antenna Base Station 454Part III Other Advanced Emerging MA Techniques for NGMA 46519 Holographic-Pattern Division Multiple Access 467Ruoqi Deng, Boya Di, and Lingyang Song19.1 Overview of HDMA 46919.2 System Model 47419.3 Multiuser Holographic Beamforming 47619.4 Holographic Pattern Design 47919.5 Performance Analysis and Evaluation 48519.6 Summary 49020 Over-the-Air Computation 495Yilong Chen, Xiaowen Cao, Jie Xu, Guangxu Zhu, Kaibin Huang, and Shuguang Cui20.1 Introduction 49520.2 AirComp Fundamentals 49720.3 Power Control for AirComp 49920.4 Beamforming for AirComp 50920.5 Extension 51420.6 Conclusion 51621 Multi-Dimensional Multiple Access for 6G: Efficient Radio Resource Utilization and Value-Oriented Service Provisioning 519Wudan Han, Jie Mei, and Xianbin Wang21.1 Introduction 51921.2 Principle of MDMA 52321.3 Value-Oriented Operation of MDMA 52821.4 Multi-Dimensional Resource Utilization in Value-Oriented MDMA 53321.5 Numerical Results and Analysis 53821.6 Conclusion 54322 Efficient Federated Meta-Learning Over Multi-Access Wireless Networks 547Sheng Yue and Ju Ren22.1 Introduction 54722.2 Related Work 54922.3 Preliminaries and Assumptions 55122.4 Nonuniform Federated Meta-Learning 55422.5 Federated Meta-Learning Over Wireless Networks 55822.6 Extension to First-Order Approximations 56822.7 Simulation 57022.8 Conclusion 577References 578Index 583