{"product_id":"next-generation-multiple-access-isbn-9781394180493","title":"Next Generation Multiple Access","description":"\u003cp\u003e\u003cb\u003eHighly comprehensive resource investigating how next-generation multiple access (NGMA) relates to unrestricted global connection, business requirements, and sustainable wireless networks\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eNext Generation Multiple Access\u003c\/i\u003e 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.\u003c\/p\u003e \u003cp\u003eThe 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.\u003c\/p\u003e \u003cp\u003eWritten by four leading experts in the field, \u003ci\u003eNext Generation Multiple Access\u003c\/i\u003e includes information on:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eFoundation and application scenarios for non-orthogonal multiple access (NOMA) systems, including modulation, detection, power allocation, and resource management\u003c\/li\u003e \u003cli\u003eNOMA's interaction with alternate applications such as satellite communication systems, terrestrial-satellite communication systems, and integrated sensing\u003c\/li\u003e \u003cli\u003eCollision resolution, compressed sensing aided massive access, latency management, deep learning enabled massive access, and energy harvesting\u003c\/li\u003e \u003cli\u003eHolographic-pattern division multiple access, over-the-air transmission, multi-dimensional multiple access, sparse signal detection, and federated meta-learning assisted resource management\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eNext Generation Multiple Access\u003c\/i\u003e 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.\u003c\/p\u003e \u003cp\u003eAbout the Editors xix\u003c\/p\u003e \u003cp\u003eList of Contributors xxiii\u003c\/p\u003e \u003cp\u003ePreface xxxiii\u003c\/p\u003e \u003cp\u003eAcknowledgments xxxv\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Next Generation Multiple Access Toward 6G 1\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eYuanwei Liu, Liang Liu, Zhiguo Ding, and Xuemin Shen\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 The Road to NGMA 1\u003c\/p\u003e \u003cp\u003e1.2 Non-Orthogonal Multiple Access 3\u003c\/p\u003e \u003cp\u003e1.3 Massive Access 4\u003c\/p\u003e \u003cp\u003e1.4 Book Outline 5\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I Evolution of NOMA Towards NGMA 9\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Modulation Techniques for NGMA\/NOMA 11\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eXuan Chen, Qiang Li, and Miaowen Wen\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 11\u003c\/p\u003e \u003cp\u003e2.2 Space-Domain IM for NGMA 12\u003c\/p\u003e \u003cp\u003e2.3 Frequency-Domain IM for NGMA 22\u003c\/p\u003e \u003cp\u003e2.4 Code-Domain IM for NGMA 31\u003c\/p\u003e \u003cp\u003e2.5 Power-Domain IM for NGMA 35\u003c\/p\u003e \u003cp\u003e2.6 Summary 43\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 NOMA Transmission Design with Practical Modulations 47\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eTianying Zhong, Yuan Wang, and Jiaheng Wang\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 47\u003c\/p\u003e \u003cp\u003e3.2 Fundamentals 49\u003c\/p\u003e \u003cp\u003e3.3 Effective Throughput Analysis 53\u003c\/p\u003e \u003cp\u003e3.4 NOMA Transmission Design 56\u003c\/p\u003e \u003cp\u003e3.5 Numerical Results 65\u003c\/p\u003e \u003cp\u003e3.6 Conclusion 68\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Optimal Resource Allocation for NGMA 71\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eSepehr Rezvani and Eduard Jorswieck\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 71\u003c\/p\u003e \u003cp\u003e4.2 Single-Cell Single-Carrier NOMA 73\u003c\/p\u003e \u003cp\u003e4.3 Single-Cell Multicarrier NOMA 80\u003c\/p\u003e \u003cp\u003e4.4 Multi-cell NOMA with Single-Cell Processing 84\u003c\/p\u003e \u003cp\u003e4.5 Numerical Results 93\u003c\/p\u003e \u003cp\u003e4.6 Conclusions 96\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Cooperative NOMA 101\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eYao Xu, Bo Li, Nan Zhao, Jie Tang, Dusit Niyato, and Kai-Kit Wong\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 101\u003c\/p\u003e \u003cp\u003e5.2 System Model for D2MD-CNOMA 102\u003c\/p\u003e \u003cp\u003e5.3 Adaptive Aggregate Transmission 103\u003c\/p\u003e \u003cp\u003e5.4 Performance Analysis 107\u003c\/p\u003e \u003cp\u003e5.5 Numerical Results and Discussion 117\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Multi-scale-NOMA: An Effective Support to Future Communication–Positioning Integration System 127\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eLu Yin, Wenfang Guo, and Tianzhu Song\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 127\u003c\/p\u003e \u003cp\u003e6.2 Positioning in Cellular Networks 128\u003c\/p\u003e \u003cp\u003e6.3 MS-NOMA Architecture 130\u003c\/p\u003e \u003cp\u003e6.4 Interference Analysis 131\u003c\/p\u003e \u003cp\u003e6.5 Resource Allocation 139\u003c\/p\u003e \u003cp\u003e6.6 Performance Evaluation 145\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 NOMA-Aware Wireless Content Caching Networks 161\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eYaru Fu, Zheng Shi, and Tony Q. S. Quek\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 161\u003c\/p\u003e \u003cp\u003e7.2 System Model 164\u003c\/p\u003e \u003cp\u003e7.3 Algorithm Design 169\u003c\/p\u003e \u003cp\u003e7.4 Numerical Simulation 173\u003c\/p\u003e \u003cp\u003e7.5 Conclusion 178\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 NOMA Empowered Multi-Access Edge Computing and Edge Intelligence 181\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eYuan Wu, Yang Li, Liping Qian, and Xuemin Shen\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 181\u003c\/p\u003e \u003cp\u003e8.2 Literature Review 183\u003c\/p\u003e \u003cp\u003e8.3 System Model and Formulation 185\u003c\/p\u003e \u003cp\u003e8.4 Algorithms for Optimal Offloading 189\u003c\/p\u003e \u003cp\u003e8.5 Numerical Results 194\u003c\/p\u003e \u003cp\u003e8.6 Conclusion 197\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Exploiting Non-orthogonal Multiple Access in Integrated Sensing and Communications 205\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eXidong Mu, Zhaolin Wang, and Yuanwei Liu\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 205\u003c\/p\u003e \u003cp\u003e9.2 Developing Trends and Fundamental Models of ISAC 206\u003c\/p\u003e \u003cp\u003e9.3 Novel NOMA Designs in Downlink and Uplink ISAC 209\u003c\/p\u003e \u003cp\u003e9.4 Case Study: System Model and Problem Formulation 213\u003c\/p\u003e \u003cp\u003e9.5 Case Study: Proposed Solutions 216\u003c\/p\u003e \u003cp\u003e9.6 Case Study: Numerical Results 219\u003c\/p\u003e \u003cp\u003e9.7 Conclusions 223\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II Massive Access for NGMA 227\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Capacity of Many-Access Channels 229\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eLina Liu and Dongning Guo\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 229\u003c\/p\u003e \u003cp\u003e10.2 The Many-Access Channel Model 231\u003c\/p\u003e \u003cp\u003e10.3 Capacity of the MnAC 232\u003c\/p\u003e \u003cp\u003e10.4 Energy Efficiency of the MnAC 240\u003c\/p\u003e \u003cp\u003e10.5 Discussion and Open Problems 253\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Random Access Techniques for Machine-Type Communication 259\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eJinho Choi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Fundamentals of Random Access 259\u003c\/p\u003e \u003cp\u003e11.2 A Game Theoretic View 263\u003c\/p\u003e \u003cp\u003e11.3 Random Access Protocols for MTC 266\u003c\/p\u003e \u003cp\u003e11.4 Variants of 2-Step Random Access 269\u003c\/p\u003e \u003cp\u003e11.5 Application of NOMA to Random Access 273\u003c\/p\u003e \u003cp\u003e11.6 Low-Latency Access for MTC 279\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Grant-Free Random Access via Compressed Sensing: Algorithm and Performance 287\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eYongpeng Wu, Xinyu Xie, Tianya Li, and Boxiao Shen\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 287\u003c\/p\u003e \u003cp\u003e12.2 Joint Device Detection, Channel Estimation, and Data Decoding with Collision Resolution for MIMO Massive Unsourced Random Access 288\u003c\/p\u003e \u003cp\u003e12.3 Exploiting Angular Domain Sparsity for Grant-Free Random Access: A Hybrid AMP Approach 294\u003c\/p\u003e \u003cp\u003e12.4 LEO Satellite-Enabled Grant-Free Random Access 301\u003c\/p\u003e \u003cp\u003e12.5 Concluding Remarks 311\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Algorithm Unrolling for Massive Connectivity in IoT Networks 315\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eYinan Zou, Yong Zhou, and Yuanming Shi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 315\u003c\/p\u003e \u003cp\u003e13.2 System Model 317\u003c\/p\u003e \u003cp\u003e13.3 Learned Iterative Shrinkage Thresholding Algorithm for Massive Connectivity 319\u003c\/p\u003e \u003cp\u003e13.4 Learned Proximal Operator Methods for Massive Connectivity 324\u003c\/p\u003e \u003cp\u003e13.5 Training and Testing Strategies 327\u003c\/p\u003e \u003cp\u003e13.6 Simulation Results 328\u003c\/p\u003e \u003cp\u003e13.7 Conclusions 331\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Grant-Free Massive Random Access: Joint Activity Detection, Channel Estimation, and Data Decoding 335\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eXinyu Bian, Yuyi Mao, and Jun Zhang\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 335\u003c\/p\u003e \u003cp\u003e14.2 System Model 337\u003c\/p\u003e \u003cp\u003e14.3 Joint Estimation via a Turbo Receiver 339\u003c\/p\u003e \u003cp\u003e14.4 A Low-Complexity Side Information-Aided Receiver 349\u003c\/p\u003e \u003cp\u003e14.5 Simulation Results 353\u003c\/p\u003e \u003cp\u003e14.6 Summary 358\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Joint User Activity Detection, Channel Estimation, and Signal Detection for Grant-Free Massive Connectivity 361\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eZhichao Shao, Shuchao Jiang, Chongbin Xu, Xiaojun Yuan, and Xin Wang\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 361\u003c\/p\u003e \u003cp\u003e15.2 Receiver Design for Synchronous Massive Connectivity 363\u003c\/p\u003e \u003cp\u003e15.3 Receiver Design for Asynchronous Massive Connectivity 372\u003c\/p\u003e \u003cp\u003e15.4 Conclusion 387\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Grant-Free Random Access via Covariance-Based Approach 391\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eYa-Feng Liu, Wei Yu, Ziyue Wang, Zhilin Chen, and Foad Sohrabi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 391\u003c\/p\u003e \u003cp\u003e16.2 Device Activity Detection in Single-Cell Massive MIMO 393\u003c\/p\u003e \u003cp\u003e16.3 Device Activity Detection in Multi-Cell Massive MIMO 402\u003c\/p\u003e \u003cp\u003e16.4 Practical Issues and Extensions 409\u003c\/p\u003e \u003cp\u003e16.5 Conclusions 411\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Deep Learning-Enabled Massive Access 415\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eYing Cui, Bowen Tan, Wang Liu, and Wuyang Jiang\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction 415\u003c\/p\u003e \u003cp\u003e17.2 System Model 419\u003c\/p\u003e \u003cp\u003e17.3 Model-Driven Channel Estimation 420\u003c\/p\u003e \u003cp\u003e17.4 Model-Driven Activity Detection 424\u003c\/p\u003e \u003cp\u003e17.5 Auto-Encoder-Based Pilot Design 429\u003c\/p\u003e \u003cp\u003e17.6 Numerical Results 431\u003c\/p\u003e \u003cp\u003e17.7 Conclusion 438\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 Massive Unsourced Random Access 443\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eVolodymyr Shyianov, Faouzi Bellili, Amine Mezghani, and Ekram Hossain\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction 443\u003c\/p\u003e \u003cp\u003e18.2 URA with Single-Antenna Base Station 444\u003c\/p\u003e \u003cp\u003e18.3 URA with Multi-Antenna Base Station 454\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart III Other Advanced Emerging MA Techniques for NGMA 465\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 Holographic-Pattern Division Multiple Access 467\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eRuoqi Deng, Boya Di, and Lingyang Song\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19.1 Overview of HDMA 469\u003c\/p\u003e \u003cp\u003e19.2 System Model 474\u003c\/p\u003e \u003cp\u003e19.3 Multiuser Holographic Beamforming 476\u003c\/p\u003e \u003cp\u003e19.4 Holographic Pattern Design 479\u003c\/p\u003e \u003cp\u003e19.5 Performance Analysis and Evaluation 485\u003c\/p\u003e \u003cp\u003e19.6 Summary 490\u003c\/p\u003e \u003cp\u003e\u003cb\u003e20 Over-the-Air Computation 495\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eYilong Chen, Xiaowen Cao, Jie Xu, Guangxu Zhu, Kaibin Huang, and Shuguang Cui\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e20.1 Introduction 495\u003c\/p\u003e \u003cp\u003e20.2 AirComp Fundamentals 497\u003c\/p\u003e \u003cp\u003e20.3 Power Control for AirComp 499\u003c\/p\u003e \u003cp\u003e20.4 Beamforming for AirComp 509\u003c\/p\u003e \u003cp\u003e20.5 Extension 514\u003c\/p\u003e \u003cp\u003e20.6 Conclusion 516\u003c\/p\u003e \u003cp\u003e\u003cb\u003e21 Multi-Dimensional Multiple Access for 6G: Efficient Radio Resource Utilization and Value-Oriented Service Provisioning 519\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eWudan Han, Jie Mei, and Xianbin Wang\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e21.1 Introduction 519\u003c\/p\u003e \u003cp\u003e21.2 Principle of MDMA 523\u003c\/p\u003e \u003cp\u003e21.3 Value-Oriented Operation of MDMA 528\u003c\/p\u003e \u003cp\u003e21.4 Multi-Dimensional Resource Utilization in Value-Oriented MDMA 533\u003c\/p\u003e \u003cp\u003e21.5 Numerical Results and Analysis 538\u003c\/p\u003e \u003cp\u003e21.6 Conclusion 543\u003c\/p\u003e \u003cp\u003e\u003cb\u003e22 Efficient Federated Meta-Learning Over Multi-Access Wireless Networks 547\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eSheng Yue and Ju Ren\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e22.1 Introduction 547\u003c\/p\u003e \u003cp\u003e22.2 Related Work 549\u003c\/p\u003e \u003cp\u003e22.3 Preliminaries and Assumptions 551\u003c\/p\u003e \u003cp\u003e22.4 Nonuniform Federated Meta-Learning 554\u003c\/p\u003e \u003cp\u003e22.5 Federated Meta-Learning Over Wireless Networks 558\u003c\/p\u003e \u003cp\u003e22.6 Extension to First-Order Approximations 568\u003c\/p\u003e \u003cp\u003e22.7 Simulation 570\u003c\/p\u003e \u003cp\u003e22.8 Conclusion 577\u003c\/p\u003e \u003cp\u003eReferences 578\u003c\/p\u003e \u003cp\u003eIndex 583\u003c\/p\u003e \u003cp\u003e\u003cb\u003eYuanwei Liu, PhD, \u003c\/b\u003eis a Senior Lecturer (Associate Professor) with the School of Electronic Engineering and Computer Science at Queen Mary University of London, UK.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eLiang Liu, PhD, \u003c\/b\u003eis an Assistant Professor in the Department of Electrical and Electronic Engineering at Hong Kong Polytechnic University.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eZhiguo Ding, PhD, \u003c\/b\u003eis a Professor in Communications with the Department of Electrical and Electronic Engineering at the University of Manchester, UK.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eXuemin Shen, PhD, \u003c\/b\u003eis a Professor with the Department of Electrical and Computer Engineering at the University of Waterloo, Canada.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eHighly comprehensive resource investigating how next-generation multiple access (NGMA) relates to unrestricted global connection, business requirements, and sustainable wireless networks\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eNext Generation Multiple Access \u003c\/i\u003eis 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.\u003c\/p\u003e \u003cp\u003eThe 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.\u003c\/p\u003e \u003cp\u003eWritten by four leading experts in the field, \u003ci\u003eNext Generation Multiple Access \u003c\/i\u003eincludes information on:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eFoundation and application scenarios for non-orthogonal multiple access (NOMA) systems, including modulation, detection, power allocation, and resource management\u003c\/li\u003e \u003cli\u003eNOMA's interaction with alternate applications such as satellite communication systems, terrestrial-satellite communication systems, and integrated sensing\u003c\/li\u003e \u003cli\u003eCollision resolution, compressed sensing aided massive access, latency management, deep learning enabled massive access, and energy harvesting\u003c\/li\u003e \u003cli\u003eHolographic-pattern division multiple access, over-the-air transmission, multi-dimensional multiple access, sparse signal detection, and federated meta-learning assisted resource management\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eNext Generation Multiple Access \u003c\/i\u003eis 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.\u003c\/p\u003e","brand":"Wiley-IEEE Press","offers":[{"title":"Default Title","offer_id":47989689745637,"sku":"NP9781394180493","price":145.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781394180493.jpg?v=1761785114","url":"https:\/\/k12savings.com\/es\/products\/next-generation-multiple-access-isbn-9781394180493","provider":"K12savings","version":"1.0","type":"link"}