mmWave massive MIMO ; a Paradigm for 5G / Editors, Shahid Mumtaz, Jonathan Rodriguez, Linglong Dai.

Format:

Book

Contributor:

Mumtaz, Shahid, editor.

Language:

English

Subjects (All):

MIMO systems.

Physical Description:

xx, 351 pages ; 24 cm

Place of Publication:

London, UK ; San Diego, CA : Academic Press, [2017]

Summary:

This book is the first of its kind to hinge together the related discussions on mmWave and Massive MIMO under the umbrella of 5G networks. New networking scenarios are identified, along with fundamental design requirements for mmWave Massive MIMO networks from an architectural and practical perspective. Working toward final deployment, this book updates the research community on the current mmWave Massive MIMO roadmap, taking into account the future emerging technologies emanating from 3GPP/IEEE. In the compilation of this book, the editors draw on their vast experience in international research and being at the forefront of mmWave Massive MIMO research arena and standardization. This book aims to talk openly about this topic and will serve as a useful reference not only for postgraduate students to learn more on this evolving field, but also to inspire mobile communication researchers toward taking further innovative strides on this field and mark their legacy in the 5G arena. Key features, Tutorials on the basics of mmWave and Massive MIMO, New 5G networking scenarios are identified, along with design requirements from an architectural and practical perspective, Contains the latest updates on the evolution of the mmWave Massive MIMO roadmap, considering future emerging technologies emanating from 3GPP/IEEE, Contributions from leading experts on the field in modeling and prototype design for mmWave Massive MIMO design, An ideal reference not only for postgraduate students to learn more on this evolving field, but also to inspire mobile communication researchers toward further innovation and mark their legacy in the 5G arena Book jacket.

Contents:

Chapter 1 Introduction to mmWave Massive MIMO / S. Mumtaz Mumtaz, S., J. Rodriguez Rodriguez, J., L. Dai Dai, L. 1

1.1 Requirements of Key Capabilities for 5G 2

1.2 5G Network Architecture Based on mmWave Massive MIMO 4

1.3 Challenges for mmWave Massive MIMO 7

1.4 Structure and Contributions of This Book 12

References 16

Chapter 2 SISO to mmWave Massive MIMO / D. Zhang Zhang, D., S. Mumtaz Mumtaz, S., K.S. Huq Huq, K.S. 19

2.1 Overview of Wireless Communication Evolution 19

2.2 The Channel Models Behind SISO, MlMO 20

2.2.1 Wireless Propagation Loss 20

2.2.2 Free Space Propagation Model 21

2.2.3 Ray Tracing 23

2.2.4 Empirical Models 25

2.2.5 Shadowing Effects 26

2.3 From SISO to MTMO 27

2.3.1 Outage Probability and Cell Coverage Area 27

2.3.2 Rayleigh and Rician Channel Models 28

2.3.3 Capacity and Transmission Rate Analysis 29

2.4 From MIMO to mMlMO 32

2.4.1 Even Faster Transmission Speed 33

2.4.2 Energy Efficiency 34

2.5 Emerging Topics in mmWave mMIMO 35

References 36

Chapter 3 Hybrid Antenna Array for mmWave Massive MIMO / J.A. Zhang Zhang, J.A., X. Huang Huang, X., V. Dyadyuk Dyadyuk, V., Y. Jay GUO Jay, Y., GUO

3.1 Introduction 39

3.2 Massive Hybrid Array Architectures 41

3.3 Hardware Design for Analog Subarray 43

3.3.1 Antenna Arrays 43

3.3.2 RF Chain Architectures 46

3.3.3 Hybrid Array Prototypes 49

3.4 Smart Antenna Techniques 51

3.4.1 Array Geometry 51

3.4.2 Pure Beamforming and AoA Estimation 52

3.4.3 Single-User MlMO 55

3.4.4 SDMA 57

3.5 Conclusions 59

References 60

Chapter 4 Encoding and Detection in mmWave Massive MIMO / S.A.R. Naqvi Naqvi, S.A.R., S.A. Hassan Hassan, S.A., Z. Mulk Mulk, Z. 63

4.1 Introduction 63

4.2 Background 64

4.3 System Model 65

4.4 Multicell Uplink Communication 67

4.4.1 Uplink Training With Pilot Reuse 67

4.4.2 Actual Transmission of Data 68

4.4.3 Achievable Cell Throughput 69

4.5 Results 72

4.6 Conclusion 77

References 77

Chapter 5 Precoding for mmWave Massive MIMO / X. Gao Gao, X., L. Dai Dai, L., Z. Gao Gao, Z., T. Xie Xie, T., Z. Wang Wang, Z. 79

5.1 Introduction 79

5.2 Channel Model for mmWave Massive MlMO 80

5.3 Digital Precoding 81

5.3.1 Single-User Digital Precoding 81

5.3.2 Multiuser Digital Precoding 83

5.3.3 Summary of Digital Precoding 84

5.4 Analog Beamforming 84

5.4.1 Beam Steering 85

5.4.2 Beam Training 86

5.4.3 Summary of Analog Beamforming 87

5.5 Hybrid Precoding 88

5.5.1 Single-User Hybrid Precoding 88

5.5.2 Multiuser Hybrid Precoding 103

5.6 Conclusions 108

References 109

Chapter 6 Channel Estimation for mmWave Massive MIMO Systems / Z. Gao Gao, Z., L. Dai Dai, L., C. Hu Hu, C., X. Gao Gao, X., Z. Wang Wang, Z. 113

6.1 Introduction 114

6.2 Preparatory Work 115

6.2.1 Channel Model 116

6.2.2 Transceiver Structure in mmWave Massive MIMO 117

6.3 Compressive Sensing (CS)-Based Channel Estimation Schemes 119

6.3.1 Concept of CS Theory 119

6.3.2 Formulate Channel Estimation as CS Problem 120

6.3.3 Sparse Channels Reconstruction Via CS 122

6.3.4 Design Training Beam and Combining Patterns According to CS Theory 123

6.3.5 Remark 125

6.4 Channel Estimation With One-Bit ADCs at the Receiver 125

6.4.1 Virtual Channel Representation of mmWave Massive MIMO Channels 126

6.4.2 The Maximal Likelihood (ML) Estimator 127

6.4.3 Estimate Channels With Iterative Approach 128

6.4.4 Remark 128

6.5 Parametric Channel Estimation Schemes for mmWave Massive MIMO Systems 129

6.5.1 Super-Resolution Sparse Channel Estimation 129

6.5.2 Multiuser and Multistream (MU-MS) Hybrid Beamforming/Combining 130

6.5.3 Numerical Simulations 132

6.5.4 Remark 134

6.6 Subspace Estimation and Decomposition (SED)-Based Channel Estimation 134

6.6.1 Subspace Estimation in Traditional MIMO Systems 134

6.6.2 Extend to Hybrid MIMO Transceiver Structure 135

6.6.3 Remark 136

6.7 Other Channel Estimation Schemes 137

6.7.1 Can Channel Estimation Schemes in Massive MIMO Be Tailored to mmWave Massive MIMO? 137

6.7.2 Codebook-Based Channel Estimation Schemes 137

6.8 Summary 138

References 138

Chapter 7 Channel Feedback for mmWave Massive MIMO / P.-H. Kuo Kuo, P.-H., B. Su Su, B., C.-P. Yen Yen, C.-P. 141

7.1 Introduction 141

7.2 Channel Feedback With Compressive Sensing 143

7.2.1 Algorithmic Framework of Compressive Sensing 144

7.2.2 Applications of Compressive Sensing to CSI Feedback Schemes 145

7.2.3 Sparsifying Basis 146

7.2.4 CSI Feedback Protocol With Adaptive Sparsifying Basis 148

7.3 CSI Acquisition With Angular-Domain Beamforming 151

7.3.1 Multistage Beamforming and Feedback 151

7.4 Downlink Precoding in FDD Based on Angle of Arrival 154

7.4.1 Background and Assumptions 156

7.4.2 Downlink Precoding Design Using Beamforming-Based Partial CSI 160

7.4.3 Simulation Results 162

7.5 Summary 163

References 166

Chapter 8 mmWave Massive MIMO Channel Modeling / B. Ai Ai, B., K. Guan Guan, K., G. Li Li, G., S. Mumtaz Mumtaz, S. 169

8.1 Introduction 169

8.2 Specific Characteristics of mmWave Massive MIMO Channels 172

8.2.1 Propagation Mechanisms of mmWave and Sub-mmWave 172

8.2.2 mmWave Massive MIMO Static Channel 173

8.2.3 mmWave Massive MIMO Dynamic Channels 180

8.3 Stale-of-the-Art of Millimeter-Wave Massive MIMO Channel Study 180

8.3.1 Millimeter-Wave Massive MIMO Channel Modeling 180

8.3.2 Millimeter-Wave Massive MIMO Channel Sounding 190

8.4 Conclusion 192

References 193

Chapter 9 mmWave Communication Enabling Techniques for 5G Wireless Systems: A Link Level Perspective / T.E. Bogale Bogale, T.E., X. Wang Wang, X., L.B. Le Le, L.B. 195

9.1 Introduction 195

9.2 Beamforming 199

9.2.1 Digital Beamforming 200

9.2.2 Hybrid Beamforming 201

9.2.3 Link Level Performance 205

9.3 Spatial Multiplexing 209

9.4 Channel Estimation 211

9.5 Waveform Design 217

9.6 Access Strategy 219

9.7 Conclusions 220

References 220

Chapter 10 MAC Layer Design for mmWave Massive MIMO / G. Lee Lee, G., Y. Sung Sung, Y. 227

10.1 Introduction 227

10.2 Basic Scheduling Algorithms 230

10.3 User Scheduling in MU-MIMO 232

10.3.1 RBF and SUS 234

10.3.2 Limited Feedback, Quantization, and Two-Phase User Scheduling 236

10.4 User Scheduling in Massive MIMO 238

10.5 User Scheduling in mmWave Massive MIMO 241

10.5.1 Randomly Directional Beamforming Under the UR-SP Channel Model 242

10.5.2 Extension to a General Sparse mmWave Channel Model 248

10.5.3 Efficient Scheduling Methods for Sparse mmWave MIMO Channels 249

10.6 Conclusions 252

References 253

Chapter 11 Enhanced Multiple-Access for mmWave Massive MIMO / M. Nasiri Khormuji Khormuji, M. Nasiri 257

11.1 Introduction 258

11.1.1 Background on mMIMO 258

11.1.2 Scope and Contributions of the Chapter 258

11.1.3 Organization of the Chapter 259

11.2 Uplink Capacity Shortage of MMIMO 259

11.3 SOMA: Novel mMIMO Uplink 262

11.3.1 Transmitter 262

11.3.2 Receiver 263

11.4 Sum-Rate Characterization of SOMA 267

11.4.1 Bounds on SOMA 267

11.4.2 Bounds on Conventional TDD 268

11.5 Numerical Evaluations of SOMA 270

11.6 Generalized SOMA 274

11.7 Two-Group GSOMA 275

11.7.1 Mode 1: Without Blanking 276

11.7.2 Mode 2: With Blanking 278

11.8 Numerical Evaluations of GSOMA 279

11.9 Conclusions 281

Appendix 281

11.A Proof of Proposition 11.1 281

11.B Proof of Proposition 11.2 283

11.C Proof of Proposition 11.3 284

11.D Proof of Proposition 11.5 285

11.E Proof of Proposition 11.6 286

References 287

Chapter 12 Fronthaul Design for mmWave Massive MIMO / Z. Gao Gao, Z., L. Dai Dai, L., X. Gao Gao, X., M.Z. Shakir Shakir, M.Z., Z.

Wang Wang, Z. 289

12.1 Introduction 290

12.2 A Survey of Existing Fronthaul Solutions 292

12.2.1 Category of Fronthaul Solutions 292

12.2.2 Fronthaul Network Topology 294

12.2.3 Pros and Cons of Different Spectrum Resources for Fronthaul 295

12.2.4 Why and How Will We Exploit mm Wave for Fronthaul? 296

12.3 Market Requirements of mmWave Fronthaul 299

12.3.1 Total Cost of Ownership (TCO) 299

12.3.2 Throughput Requirement of Fronthaul Network 300

12.3.3 Traffic Classes and Latency 301

12.3.4 Intercell/Intersite Distance (ISO) 302

12.4 mmWave Massive MIMO-Based Fronthaul Solution 303

12.4.1 Concept of mmWave Massive MIMO-Based Fronthaul 303

12.4.2 Antenna Techniques 304

12.4.3 Reliable Channel Estimation Schemes 306

12.4.4 Flexible Beamforming Design 308

12.4.5 Time Division Duplex (TDD), Frequency Division Duplex (FDD), or Full Duplex? 309

12.4.6 In-Band, Out-Band, or Hybrid-Band 310

12.5 Summary 311

References 311

Chapter 13 mmWave Cellular Networks: Stochastic Geometry Modeling, Analysis, and Experimental Validation / W. Lu Lu, W., M. Di Renzo Renzo, M. Di 313

13.1 Introduction 314

13.2 System Model 315

13.2.1 PPP-Based Abstraction Modeling 315

13.2.2 Directional Beamforming Modeling 316

13.2.3 Link State Modeling 317

13.2.4 Path-Loss Modeling 317

13.2.5 Shadowing Modeling 318

13.2.6 Cell Association Criterion 318

13.2.7 Problem Formulation 319

13.3 Preliminaries: Analysis and Approximations of Transformations of the Path-Loss 320

13.3.1 Two-Ball Approximation 321

13.3.2 Communication Blockage Probability 324

13.4 Modeling Coverage and Rate: Noise-Limited Approximation 325

13.5 Modeling Coverage and Rate: Accurate Modeling of the Other-Cell Interference 326

13.6 Numerical and Simulation Results 329

13.6.1 Experimental Validation of PPP-Based Modeling 329

13.6.2 Validation of the Noise-Limited Approximation 331

13.7 Conclusion 336

Appendix 336

13.A Proofs of the Results in Section 13.3 336

13.B Proofs of the Results in Section 13.4 337

13.C Proofs of the Results in Section 13.5 338

References 339.

ISBN:

9780128044186

0128044187

OCLC:

967766156