Le-Ngoc / Mai Hybrid Massive MIMO Precoding in Cloud-RAN

1. Auflage 2018
ISBN: 978-3-030-02158-0
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 162 Seiten

Reihe: Wireless Networks

This book covers the design and optimization of hybrid RF-baseband precoding for massive multiple-input multiple-output (MIMO)-enabled cloud radio access networks (RANs), where use cases such as millimeter-wave wireless backhauling, fully-loaded cellular networks are of interest. The suitability and practical implementation of the proposed precoding solutions for the Cloud RAN architecture are also discussed.Novel techniques are examined for RF precoding optimization in combination with nonlinear precoding at baseband, and the superiority of joint RF-baseband design is verified. Moreover, the efficacy of hybrid RF-baseband precoding to combat intercell interference in a multi-cell environment with universal frequency reuse is investigated, which is concluded to be a promising enabler for the dense deployment of base stations. This book mainly targets researchers and engineers interested in the challenges, optimization, and implementation of massive MIMO precoding in 5G Cloud RAN. Graduate students in electrical engineering and computer science interested in the application of mathematical optimization to model and solve precoding problems in massive MIMO cellular systems will also be interested in this book.

Autoren/Hrsg.

Le-Ngoc, Tho

Mai, Ruikai

Inhaltsverzeichnis

1;Preface;6
2;Contents;8
3;List of Acronyms;11
4;List of Symbols;13
5;List of Notations;14
6;1 Introduction;16
6.1;1.1 Scaling up MIMO Communications;16
6.2;1.2 Massive MIMO: Architecture, Challenges, and Opportunities;18
6.2.1;1.2.1 Hardware Architecture;18
6.2.2;1.2.2 Challenges and Opportunities;20
6.3;1.3 Theme and Organization of Monograph;22
6.4;References;25
7;2 Background;26
7.1;2.1 Linear Precoding and Combining for Point-to-Point MIMO;26
7.1.1;2.1.1 Baseband Digital Solutions for Conventional MIMO;26
7.1.2;2.1.2 Progressive Baseband Digital Solutions for Conventional MIMO ARQ;27
7.1.3;2.1.3 Hybrid RF-Baseband Solutions for Massive MIMO;29
7.2;2.2 Multi-User MIMO Precoding;33
7.2.1;2.2.1 Precoding for Conventional MIMO: From Linear to Nonlinear;33
7.2.2;2.2.2 Hybrid RF-Baseband Solutions for Massive MIMO;36
7.3;2.3 Summary;39
7.4;References;40
8;3 Hybrid Precoding and Combining for Massive MIMO Wireless Backhauling;44
8.1;3.1 Introduction;44
8.2;3.2 System Model and Problem Statement;45
8.3;3.3 Joint Nonuniform-Modulus RF Tx-Rx Design;52
8.4;3.4 RF Phase-Shifting Design by Matrix Reconstruction;55
8.4.1;3.4.1 Magnitude LS Formulation;55
8.4.2;3.4.2 AJD-Based Solution;58
8.5;3.5 Illustrative Results and Discussions;60
8.5.1;3.5.1 Simulation Setup;60
8.5.2;3.5.2 Effect of Limited RF Chains;61
8.5.3;3.5.3 Effect of Delay-Outage Constraints;63
8.5.4;3.5.4 Effect of Angle Spread;64
8.5.5;3.5.5 Computational Complexity;65
8.6;3.6 Summary;66
8.7;Appendix 1: Proof of Theorem 3.1;67
8.8;Appendix 2: Proof of Corollary 3.1;68
8.9;Appendix 3: Proof of Theorem 3.2;69
8.10;Appendix 4: Proof of Theorem 3.3;70
8.11;References;71
9;4 Hybrid Precoding/Combining for Massive MIMOwith Hybrid ARQ;73
9.1;4.1 Introduction;73
9.2;4.2 System Model and Problem Statement;74
9.3;4.3 Progressive Hybrid Precoding Design;78
9.4;4.4 Progressive Hybrid Combining Design;81
9.5;4.5 Illustrative Results and Discussions;83
9.5.1;4.5.1 Small M;84
9.5.2;4.5.2 Large M;85
9.5.3;4.5.3 Increasing Number of RF Chains;86
9.5.4;4.5.4 Impact of Angle Spread;87
9.5.5;4.5.5 Quantization of RF Precoder/Combiner;88
9.5.6;4.5.6 MSE;89
9.5.7;4.5.7 Complexity;90
9.6;4.6 Summary;90
9.7;Appendix 1: Proof of Theorem 4.1;91
9.8;References;94
10;5 Nonlinear Hybrid Precoding for Massive MIMO with Fractional Frequency Reuse;95
10.1;5.1 Introduction;95
10.2;5.2 System Model and Problem Statement;97
10.3;5.3 Joint Hybrid MMSE-VP Precoding;100
10.3.1;5.3.1 MSE-Based Problem Formulation;100
10.3.2;5.3.2 Statistical CSI-Based RF Precoding Design;102
10.3.2.1;5.3.2.1 Single-Cluster Transmission;102
10.3.2.2;5.3.2.2 Multi-Cluster Transmission;102
10.3.3;5.3.3 Statistical CSI-Based RF Phase-Shifting Design;106
10.4;5.4 Cluster-Wise Hybrid MMSE-VP Precoding;109
10.4.1;5.4.1 MSE-Based Problem Formulation;109
10.4.2;5.4.2 Modified MSE-Based RF Precoding Design;111
10.4.3;5.4.3 Statistical CSI-Based RF Phase-Shifting Design;113
10.5;5.5 Illustrative Results and Discussions;116
10.5.1;5.5.1 Simulation Setup;116
10.5.2;5.5.2 Single-Cluster Scenario;117
10.5.3;5.5.3 Multi-Cluster Scenario;118
10.6;5.6 Summary;121
10.7;Appendix 1: Proof of Theorem 5.1;122
10.8;Appendix 2: Proof of Lemma 5.1;123
10.9;Appendix 3: Proof of Theorem 5.2;123
10.10;Appendix 4: Derivation of Riemannian Gradient and Riemannian Hessian;124
10.10.1;Joint Hybrid MMSE-VP Precoding;124
10.10.2;Cluster-Wise Hybrid MMSE-VP Precoding;125
10.11;Appendix 5: Proof of Proposition 5.1;126
10.12;Appendix 6: Proof of Lemma 5.2 and Lemma 5.3;127
10.13;References;127
11;6 Nonlinear Hybrid Precoding for Massive MIMO with Universal Frequency Reuse;129
11.1;6.1 Introduction;129
11.2;6.2 System Model and Problem Statement;132
11.3;6.3 Hybrid Precoder Design with Centralized MMSE-VP;135
11.3.1;6.3.1 Robust Centralized Baseband Precoding;135
11.3.2;6.3.2 Joint RF-Baseband Precoding;140
11.4;6.4 Hybrid Precoder Design with Distributed MMSE-VP;145
11.4.1;6.4.1 Approximate BD-Based RF Beamforming;145
11.4.2;6.4.2 Robust Distributed Baseband Precoding;146
11.4.3;6.4.3 Joint RF-Baseband Precoding;147
11.5;6.5 Illustrative Results and Discussions;149
11.5.1;6.5.1 Simulation Setup;149
11.5.2;6.5.2 Performance Evaluation;150
11.6;6.6 Summary;152
11.7;Appendix 1: Proof of Theorem 6.1;154
11.8;Appendix 2: Proof of Theorem 6.2;154
11.9;References;156
12;7 Conclusions;158
12.1;7.1 Integration of Hybrid Precoding with C-RAN;158
12.2;7.2 Future Work;160
12.3;References;162