Multiple Access Techniques for 5G Wireless Networks and Beyond (eBook)

Mojtaba Vaezi, Zhiguo Ding, H. Vincent Poor (Herausgeber)

eBook Download: PDF

2018 | 1st ed. 2019
XXIII, 685 Seiten
Springer International Publishing (Verlag)
978-3-319-92090-0 (ISBN)

Infos

This book presents comprehensive coverage of current and emerging multiple access, random access, and waveform design techniques for 5G wireless networks and beyond. A definitive reference for researchers in these fields, the book describes recent research from academia, industry, and standardization bodies. The book is an all-encompassing treatment of these areas addressing orthogonal multiple access and waveform design, non-orthogonal multiple access (NOMA) via power, code, and other domains, and orthogonal, non-orthogonal, and grant-free random access. The book builds its foundations on state of the art research papers, measurements, and experimental results from a variety of sources.

Mojtaba Vaezi received the Ph.D. degree in Electrical Engineering from McGill University in 2014. Since 2015 he has been with Princeton University as a Postdoctoral Research Fellow and Associate Research Scholar. He is currently an Assistant Professor of ECE at Villanova University and a Visiting Research Collaborator at Princeton University. Before joining Princeton, he was a researcher at Ericsson Research in Montreal, Canada. His research interests include the broad areas of information theory, wireless communications, and signal processing, with an emphasis on physical layer security and radio access technologies. Among his publications in these areas is the book Cloud Mobile Networks: From RAN to EPC (Springer, 2017). Dr. Vaezi has served as the president of McGill IEEE Student Branch during 2012-2013. He is an Associate Editor of IEEE Communications Magazine and IEEE Communications Letters. He has co-organized four international NOMA workshops at VTC-Spring'17, Globecom'17, ICC'18, and Globecom'18. Dr. Vaezi is a recipient of a number of academic, leadership, and research awards, including McGill Engineering Doctoral Award, IEEE Larry K. Wilson Regional Student Activities Award in 2013, the Natural Sciences and Engineering Research Council of Canada (NSERC) Postdoctoral Fellowship in 2014, and Ministry of Science and ICT of Korea's best paper award in 2017.

Zhiguo Ding received his B.Eng. in Electrical Engineering from the Beijing University of Posts and Telecommunications in 2000, and the Ph.D. degree in Electrical Engineering from Imperial College London in 2005. From Jul. 2005 to Apr. 2018, he was working in Queen's University Belfast, Imperial College, Newcastle University and Lancaster University. Since Apr. 2018, he has been with the University of Manchester as a Professor in Communications. From Sept. 2012 to Sept. 2018, he has also been an academic visitor in Princeton University. Dr. Ding's research interests are 5G networks, game theory, cooperative and energy harvesting networks and statistical signal processing. He is serving as an Editor for IEEE Transactions on Communications and IEEE Transactions on Vehicular Technology. He served as an Editor for IEEE Wireless Communication Letters, IEEE Communication Letters, and Journal of Wireless Communications and Mobile Computing. He received the best paper award in IET Comm. Conf. on Wireless, Mobile and Computing, 2009 and the IEEE WCSP 2015, IEEE Transactions on Vehicular Technologies Top Editor 2017, and the EU Marie Curie Fellowship 2012-2014.

H. Vincent Poor received the Ph.D. degree in EECS from Princeton University in 1977. From 1977 until 1990, he was on the faculty of the University of Illinois at Urbana-Champaign. Since 1990 he has been on the faculty at Princeton, where he is currently the Michael Henry Strater University Professor of Electrical Engineering. During 2006 to 2016, he served as Dean of Princeton's School of Engineering and Applied Science. His research interests are in the areas of information theory and signal processing, and their applications in wireless networks, energy systems and related fields. Dr. Poor is a member of the National Academy of Engineering and the National Academy of Sciences, and is a foreign member of the Chinese Academy of Sciences, the Royal Society, and other national and international academies. Other recognition of his work includes the 2017 IEEE Alexander Graham Bell Medal, and honorary doctorates and professorships from a number of universities,

Inhalt

Preface 5
Contents 8
About the Editors 10
Acronyms 12
Part I Orthogonal Multiple Access Techniques and Waveform Design 23
1 Introduction to Cellular Mobile Communications 24
1.1 Introduction 24
1.2 Cellular Mobile Communication: A Primer 25
1.2.1 The Evolution of Mobile Technologies 28
1.2.2 First-Generation Cellular Systems 29
1.2.3 Second-Generation Cellular Systems 30
1.2.4 Third-Generation Cellular Systems 32
1.2.5 Fourth-Generation Cellular Systems 38
1.3 5G Drivers, Technologies, and Spectrum 43
1.3.1 5G Drivers 44
1.3.2 5G Technologies 46
1.3.3 5G Spectrum and mm-Wave Band 51
1.4 Waveform Design for 5G 53
1.5 Multiple Access Techniques in 1G to 5G 54
1.6 What is Non-Orthogonal Multiple Access? 55
1.7 Conclusion 57
References 57
2 OFDM Enhancements for 5G Based on Filtering and Windowing 59
2.1 Motivation 59
2.1.1 Multi-carrier Transmission 60
2.2 5G Waveform Requirements and Scenarios 63
2.2.1 Mixed Numerology 64
2.2.2 Asynchronous Uplink Transmission 65
2.3 Candidate 5G Waveforms 65
2.3.1 Weighted Overlap and Add (WOLA) 68
2.3.2 Universal Filtered OFDM (UF-OFDM) 69
2.3.3 Filtered OFDM (f-OFDM) 72
2.3.4 Comparison Between the Different Waveforms 73
2.4 Summary 78
References 79
3 Filter Bank Multicarrier Modulation 82
3.1 Why FBMC? 82
3.2 Multicarrier Modulation 84
3.2.1 CP-OFDM 87
3.3 FBMC-OQAM 88
3.3.1 Latency 91
3.3.2 Channel Estimation 92
3.4 Discrete-Time System Model 92
3.4.1 IFFT Implementation 94
3.5 One-Tap Equalizers in Doubly Selective Channels 96
3.6 Block Spread FBMC: Enabling All MIMO Methods 100
3.7 Pruned DFT-Spread FBMC-OQAM: Reducing the PAPR 106
3.8 Summary 108
References 109
4 Generalized Frequency Division Multiplexing: A Flexible Multicarrier Waveform 112
4.1 Introduction to GFDM Modulator 112
4.1.1 Continuous Signal Model 113
4.1.2 Discrete Signal Model 115
4.1.3 GFDM Matrix Decomposition 118
4.1.4 Performance Indicators 121
4.1.5 GFDM Pulse Shaping Filter Design 124
4.1.6 Multicarrier Waveforms Generator 132
4.1.7 Channel Estimation for GFDM Detection 137
4.1.8 Transmission Diversity for GFDM 146
4.2 Link-Level Waveform Comparison 148
4.2.1 System Configurations 150
4.2.2 OOB Emission 152
4.2.3 PAPR 153
4.2.4 FER Under a Doubly Dispersive Channel 154
4.2.5 FER with Imperfect Synchronization and Channel Estimation 156
4.2.6 Section Summary 157
4.3 Multiple Access with GFDM 157
4.3.1 Signal Model 158
4.3.2 Frequency Domain Processing 160
4.3.3 Asynchronous MA Evaluation 163
4.3.4 Mixed-Numerology with GFDM 166
4.4 GFDM Implementation 170
4.4.1 Modem Implementation 171
4.4.2 Complete Transceiver Chain and Extension for MIMO 174
References 180
Part II Non-Orthogonal Multiple Access (NOMA) in the Power Domain 183
5 NOMA: An Information-Theoretic Perspective 184
5.1 What Is Non-Orthogonal Multiple Access (NOMA)? 184
5.2 What Drives NOMA? 187
5.3 Theory Behind NOMA 190
5.3.1 Single-Cell NOMA 190
5.3.2 Multi-Cell NOMA 195
5.3.3 NOMA in MIMO Networks 198
5.4 Moving from Theory to Practice 200
5.4.1 SIC in 4G Networks 201
5.4.2 Multi-Cell NOMA Solutions 202
5.5 Physical Layer Security in NOMA 203
5.5.1 Description of the Channel Models 203
5.5.2 Physical Layer Security via Beamforming 206
5.5.3 Research Directions 207
References 208
6 Optimal Power Allocation for Downlink NOMA Systems 211
6.1 Introduction 211
6.2 Fundamentals of Downlink NOMA 212
6.3 Two-User NOMA 215
6.3.1 Optimal Power Allocation for MMF 215
6.3.2 Optimal Power Allocation for SR Maximization 216
6.3.3 Optimal Power Allocation for EE Maximization 218
6.4 MU-NOMA 221
6.4.1 Optimal Power Allocation for MMF 221
6.4.2 Optimal Power Allocation for SR Maximization 222
6.4.3 Optimal Power Allocation for EE Maximization 225
6.5 MC-NOMA 227
6.5.1 Optimal Power Allocation for MMF 228
6.5.2 Optimal Power Allocation for SR Maximization 229
6.5.3 Optimal Power Allocation for EE Maximization 231
6.6 Numerical Results 235
6.7 Conclusion 238
References 241
7 On the Design of Multiple-Antenna Non-Orthogonal Multiple Access 244
7.1 Introduction 244
7.2 System Model and Framework Design 246
7.2.1 User Clustering 246
7.2.2 CSI Acquisition 247
7.2.3 Superposition Coding and Transmit Beamforming 249
7.2.4 Successive Interference Cancellation 250
7.3 Performance Analysis and Optimization 250
7.3.1 Average Transmission Rate 251
7.3.2 Power Allocation 253
7.3.3 Feedback Distribution 256
7.3.4 Mode Selection 257
7.3.5 Joint Optimization Scheme 258
7.4 Asymptotic Analysis 259
7.4.1 Interference Limited Case 259
7.4.2 Noise-Limited Case 264
7.5 Simulation Results 264
7.6 Conclusion 268
References 269
8 NOMA for Millimeter Wave Networks 272
8.1 Introduction 272
8.2 Fundamentals of mmWave Communications 273
8.2.1 Path Loss and Small-Scale Fading 273
8.2.2 Directivity Gain 274
8.2.3 User Association 274
8.3 Unicast Transmissions for mmWave-NOMA Networks 275
8.3.1 System Model 276
8.3.2 Performance Analysis 277
8.3.3 Numerical Results 281
8.4 Multicast Transmissions for mmWave-NOMA Networks 284
8.4.1 System Model 285
8.4.2 Performance Analysis 286
8.4.3 Numerical Results 289
8.5 Cooperative Multicast Transmissions for mmWave-NOMA HetNets 291
8.5.1 System Model 292
8.5.2 Performance Analysis 293
8.5.3 Numerical Results 295
8.6 Summary 296
References 298
9 Full-Duplex Non-Orthogonal Multiple Access Networks 300
9.1 Introduction 300
9.2 Full-Duplex NOMA Networks 301
9.2.1 Preliminaries 301
9.2.2 Challenges of FD-NOMA Resource Optimization 304
9.2.3 User Pairing and Power Optimization 304
9.2.4 Optimization Tools 307
9.3 State of the Art in FD and NOMA Resource Optimization 308
9.3.1 FD Resource Optimization 308
9.3.2 NOMA Resource Optimization 309
9.3.3 FD-NOMA Resource Optimization 311
9.4 Numerical Results 311
9.5 Conclusions and Open Problems 315
References 316
10 Heterogeneous NOMA with Energy Cooperation 319
10.1 Background 319
10.1.1 Resource Allocation in NOMA HetNets 319
10.1.2 Energy Cooperation 320
10.2 Network Model and Problem Formulation 321
10.2.1 Downlink NOMA Transmission 322
10.2.2 Energy Model 324
10.2.3 Problem Formulation 325
10.3 Proposed Resource Allocation Scheme 326
10.3.1 Resource Allocation Under Fixed Transmit Power 326
10.3.2 Resource Allocation Under Power Control 332
10.3.3 Comparison with FTPA 334
10.3.4 Comparison with No Renewable Energy 334
10.3.5 Comparison with No Energy Cooperation 335
10.4 Simulation Results 335
10.4.1 User Association Under Fixed Transmit Power 335
10.4.2 Power Control Under Fixed User Association 338
10.4.3 Joint User Association and Power Control 340
10.5 Conclusion and Future Work 342
References 342
11 NOMA in Vehicular Communications 346
11.1 Background and Motivation 346
11.1.1 Overview of LTE-Based V2X 347
11.1.2 The Applicability of NOMA to V2X Communications 349
11.1.3 The Applicability of SM to V2X Communications 350
11.1.4 NOMA-SM Tailored for Vehicular Communications 351
11.1.5 Outline of the Chapter 352
11.2 System Model 352
11.2.1 The Principles of NOMA-SM 354
11.2.2 V2V Massive MIMO Channel Model 356
11.3 Capacity Analysis of the NOMA-SM System 357
11.3.1 Capacity Analysis of the Collaboration-Aided Vehicle 357
11.3.2 Capacity Analysis of the In-Car User 358
11.3.3 Mutual Information 359
11.3.4 An Illustration 361
11.4 Power Allocation Algorithms 362
11.4.1 Problem Formulation 363
11.4.2 The Proposed Power Allocation Algorithm 365
11.5 Simulations and Discussions 367
11.5.1 BER Results and Discussions 368
11.5.2 Capacity Results and Discussions 371
11.6 Chapter Summary and Future Outlook 375
References 376
Part III NOMA in Code and Other Domains 380
12 Sparse Code Multiple Access (SCMA) 381
12.1 General Description 381
12.1.1 System Model 382
12.1.2 Multi-user Detection 386
12.2 Performance Evaluation 390
12.2.1 Average Error Probability 390
12.2.2 Capacity and Cutoff Rate 400
12.3 Codebook Design 405
12.3.1 General Design Rules 406
12.3.2 Multi-user Codebooks Design for Uplink SCMA Systems 411
12.3.3 Low-Projected Multi-dimensional Constellations Design 415
12.4 SCMA for 5G Radio Transmission 425
12.4.1 Application Scenarios for 5G Networks 425
12.4.2 Challenges and Future Works 426
References 426
13 Interleave Division Multiple Access (IDMA) 429
13.1 Overview 429
13.2 Basic Principles of IDMA 432
13.2.1 IDMA Transmitter Principles 433
13.2.2 Operations on a Multiple Access Node 435
13.2.3 Overall IDMA Receiver 438
13.2.4 Performance Evaluation Through SNR Evolution 440
13.2.5 Superposition Coded Modulation (SCM) 441
13.3 Power Control for IDMA 442
13.3.1 Transmitted and Received Power Minimization 442
13.3.2 Feasible Profile 443
13.3.3 Greedy Search 443
13.3.4 Approximate Linear Programming Method 444
13.4 Random Access via IDMA 446
13.4.1 Limitations of Conventional Systems 446
13.4.2 Random IDMA with Decentralized Power Control 446
13.5 IDMA in MIMO Systems 450
13.5.1 Multi-User Gain in MIMO Systems 450
13.5.2 Iterative Maximum Ratio Combining (I-MRC) 451
13.5.3 Data-Aided Channel Estimation (DACE) 452
13.6 Prospective Applications of IDMA in 5G Systems 454
13.7 Summary 457
References 457
14 Pattern Division Multiple Access (PDMA) 462
14.1 Origination and Principles of PDMA 462
14.1.1 Error Propagation Problem in SIC 463
14.1.2 Transmitter and Receiver Joint Design 463
14.1.3 PDMA Definition and Framework 465
14.1.4 PDMA Transmitting and Receiving Scheme 467
14.2 Pattern Design of PDMA 468
14.2.1 Basic Pattern Matrix 469
14.2.2 Pattern Optimization Method 470
14.2.3 PDMA Pattern for 5G eMBB Scenario 472
14.2.4 PDMA Pattern for 5G mMTC Scenario 474
14.3 Receiver Algorithms of PDMA 475
14.3.1 Successive Interference Cancellation 475
14.3.2 Belief Propagation (BP) 476
14.3.3 BP Based Iterative Detection and Decoding (BP-IDD) 478
14.3.4 Expectation Propagation (EP) 478
14.3.5 Comparison of Different Receivers 481
14.4 PDMA Performance 481
14.4.1 Link Level Simulation (LLS) 481
14.4.2 System-Level Simulation (SLS) 485
14.5 Extension Design of PDMA 486
14.5.1 PDMA Based Grant Free Transmission 486
14.5.2 Cooperative PDMA 488
14.5.3 PDMA Combing with Massive MIMO 490
14.5.4 PDMA Combing with Interleaving 491
14.5.5 PDMA Combing with Polar Coding 494
14.6 PDMA Applications 497
14.6.1 Application Scenarios 497
14.6.2 System Design Aspects 499
14.7 Challenges and Trends 500
References 502
15 Low Density Spreading Multiple Access 504
15.1 Motivations for Low Density Spreading 504
15.1.1 Code Division Multiple Access (CDMA) 504
15.1.2 Low Density Spreading CDMA 507
15.2 Multicarrier Low Density Spreading Multiple Access 510
15.2.1 MC-LDSMA System Model 510
15.2.2 MC-LDSMA Properties in Comparison with Other Multiple Access Techniques 516
15.3 Challenges and Optimization Opportunities for LDS 518
15.3.1 Envelope Fluctuations in LDS Multiple Access 518
15.3.2 Radio Resource Allocation for LDS 520
15.4 Summary 523
References 524
16 Grant-Free Multiple Access Scheme 526
16.1 Motivation 526
16.1.1 On Grant-Free Multiple Access 527
16.1.2 Grant-Free Key Technical Components 527
16.2 Grant-Free Transmission 529
16.2.1 Resource Configuration 529
16.2.2 HARQ Procedure 531
16.2.3 Contention and Resolution 533
16.3 Performance Analysis and Evaluation 536
16.3.1 Reliability with Repetitions 536
16.3.2 UE Activity Detection 538
16.3.3 Grant-Free and NOMA Performance 539
16.4 Conclusion and Summary 542
References 543
17 Random Access Versus Multiple Access 545
17.1 Current Random Access (RA) Schemes 545
17.1.1 Carrier Sensing Protocols 546
17.1.2 Distributed Reservation Protocols 547
17.1.3 ALOHA Protocols 548
17.2 5G NOMA-Based RA Proposals for IoT 556
17.2.1 Codebook-Based MA 558
17.2.2 Sequence-Based MA 560
17.2.3 Interleaver/Scrambled-Based MA 564
17.3 Additional NOMA-Based RA Schemes for IoT 566
17.3.1 Slotted RA Solutions 566
17.3.2 Unslotted RA Solutions 579
References 590
Part IV Challenges, Solutions, and Future Trends 595
18 Experimental Trials on Non-Orthogonal Multiple Access 596
18.1 Introduction 596
18.2 Downlink NOMA 597
18.2.1 Concept 597
18.2.2 Receiver 597
18.3 Combination of Downlink NOMA and MIMO 599
18.3.1 Concept 599
18.3.2 Transceiver Design for Downlink NOMA Combined with SU-MIMO 602
18.3.3 Combination of Downlink NOMA with Open-Loop SU-MIMO 604
18.4 Link-Level Evaluation and Experiment Parameters 606
18.5 Link-Level Performance Evaluation with Different Receivers 607
18.6 NOMA Experimental Trials 608
18.6.1 Test Bed Using Fading Emulator 608
18.6.2 Configurations of Outdoor and Indoor Experimental Trials 609
18.7 Trial Results 611
18.7.1 Indoor Experiments 611
18.7.2 Outdoor Experiments 614
18.8 Conclusion 615
References 616
19 Non-Orthogonal Multiple Access in LiFi Networks 617
19.1 A Brief Introduction to Visible Light Communication 617
19.2 System Model 619
19.2.1 Channel Model 619
19.2.2 Application of NOMA to LiFi 621
19.3 Performance Evaluation 627
19.3.1 Distribution Functions of the Channel Gain 627
19.3.2 Case 1: Guaranteed Quality of Service 628
19.3.3 Case 2: Opportunistic Best-Effort Service 629
19.4 Impact of User Pairing 633
19.4.1 Impact of User Pairing on Individual Rates 633
19.4.2 Impact of User Pairing on the Sum Rate 635
19.5 Simulation Results 639
19.5.1 Theoretical Framework 639
19.5.2 Multipath Reflections and Shadowing Effect 643
19.6 Summary and Future Works 644
References 645
20 NOMA-Based Integrated Terrestrial-Satellite Networks 647
20.1 Background 647
20.2 System Model and Problem Formulation 650
20.3 User Paring Scheme 655
20.3.1 Selection of Satellite User 655
20.3.2 Terrestrial User Paring Scheme 656
20.4 Terrestrial Resource Allocation 659
20.4.1 Terrestrial Beamforming 659
20.4.2 Intra-group Power Allocation 660
20.4.3 Inter-group Power Allocation 662
20.5 Satellite Resource Allocation 664
20.5.1 Satellite Beamforming 665
20.5.2 Satellite Power Allocation 666
20.5.3 Joint Power Allocation 668
20.6 Performance Evaluation 669
20.7 Conclusion 674
References 675
21 Conclusions and Future Research Directions for NOMA 677
21.1 Summary 677
21.2 Open Issues and Future Research Challenges 678
21.2.1 A New Era of Hybrid Multiple Access 678
21.2.2 Combination of NOMA with Other Advanced Physical Layer Designs 680
21.3 Integrating NOMA into Systems Beyond Cellular Communications 683
References 684
Index 686

Produkt-Details

• Erscheint lt. Verlag: 23.8.2018
• Zusatzinfo: XXIII, 685 p. 298 illus., 209 illus. in color.
• Verlagsort: Cham
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik
• Themenwelt: Technik ► Elektrotechnik / Energietechnik
• Themenwelt: Technik ► Maschinenbau
• Schlagworte: 5G • Code Division Multiple Access (CDMA) • filter bank multi-carrier (FBMC) • filtered OFDM (F-OFDM) • frequency division multiple access (FDMA) • generalized frequency division multiplexing (GFDM) • interleave division multiple access (IDMA) • lattice partition multiple access (LPMA) • Long-Term Evolution (LTE) • multiple access • multi-user shared access (MUSA) • non-orthogonal multiple access (NOMA) • orthogonal frequency-division multiple access (OFDMA) • sparse code multiple access (SCMA) • time division multiple access (TDMA) • universal filtered multicarrier (UFMC)
• ISBN-10: 3-319-92090-1 / 3319920901
• ISBN-13: 978-3-319-92090-0 / 9783319920900