Stochastic Geometry Analysis of Multi-Antenna Wireless Networks

Table of Contents

1 Introduction 1

[Give the background and motivation of this book]

1.1 What is 5G Wireless Network? 1

1.2 Paving the Way for 5G Networks 3

1.2.1 High Speed: Spectral Efficiency 4

1.2.2 Green Networking: Energy Efficiency 5

1.2.3 Small Cell: Ultra Dense Networks 6

1.2.4 New Spectrum: Beyond Sub-6 GHz 7

1.3 Network Analysis via Stochastic Geometry 8

1.4 Book Outline 10

 

2 Fundamentals of Wireless Networks 12

[Provide some mathematical basics for network analysis]

2.1 Spatial Model of Wireless Networks 12

2.1.1 Stochastic Geometry 12

2.1.2 Point Process 14

2.1.3 Sums and Products over Point Processes 17

2.1.4 Poisson Network Model 20

2.2 Network Performance Metrics 24

2.3 Performance Analysis in Poisson Networks 28

2.3.1 Shot Noise 28

2.3.2 Interference Characterization 32

2.3.3 SINR Distribution and Coverage 37

2.4 Multi-Antenna Techniques 42

2.4.1 MIMO Transmission Schemes 47

2.4.2 Signal and Interference Distributions 52

 

3 A Framework for Analyzing Multi-Antenna Wireless Networks 57

[Present a general analytical framework for multi-antenna networks]

3.1 A General Framework for Analysis of Multi-Antenna Networks 57

3.1.1 Network Model 57

3.1.2 Analytical Framework 62

3.1.3 Single-Antenna vs. Multi-Antenna Networks 72

3.2 Analysis for Multi-Antenna Networks 77

3.2.1 Cellular Networks 82

3.2.2 Ad Hoc Networks 87

3.3 Properties in General Multi-Antenna Networks 92

3.3.1 Densification: Impact of BS density 92

3.3.2 MIMO: Impact of Multiple Antennas 97

 

Xianghao Yu received his B.Eng. degree in Information Engineering from Southeast University, Nanjing, China, in 2014, and his Ph.D. degree in Electronic and Computer Engineering from the Hong Kong University of Science and Technology (HKUST), Kowloon, Hong Kong, in 2018. His research interests include millimeter wave communications, MIMO systems, mathematical optimization, and stochastic geometry. He was the recipient of the IEEE GLOBECOM 2017 Best Paper Award.
Chang Li received his B.Eng. degree in Information and Communication Engineering from Xi'an Jiaotong University, Xi'an, China, in 2010, and his Ph.D. degree in Electrical and Computer Engineering from the Hong Kong University of Science and Technology (HKUST), Kowloon, Hong Kong, in 2016. From February 2015 to January 2016, he was a Visiting Student at the Laboratory for Information and Decision Systems (LIDS), Massachusetts Institute of Technology (MIT), Cambridge, MA, USA. He is currently a guest researcher with the Advanced Network Technologies Division (ANTD), National Institute of Standards and Technology (NIST). His research interests include network localization and navigation, heterogeneous networks, MIMO systems, green communications, and the application of stochastic geometry.
Jun Zhang received his Ph.D. degree in Electrical and Computer Engineering from the University of Texas at Austin. He is currently an Assistant Professor at the Department of Electronic and Information Engineering at the Hong Kong Polytechnic University. Dr. Zhang co-authored the book Fundamentals of LTE (Prentice-Hall, 2010). He is a co-recipient of the 2016 Marconi Prize Paper Award in Wireless Communications, the 2014 Best Paper Award for the EURASIP Journal on Advances in Signal Processing, an IEEE GLOBECOM Best Paper Award in 2017, an IEEE ICC Best Paper Award in 2016, and an IEEE PIMRC Best Paper Award in 2014. One paper he co-authored received the 2016 IEEE Signal Processing Society Young Author Best Paper Award. He

"The most remarkable aspect of the book is the reader-friendly structure and the style in which it has been written. This book is suitable for both beginners in wireless network analysis and experienced researchers who intend to work in depth on the performance analysis of multi-antenna wireless networks. The importance of this book both from the practical and from the theoretical standpoint is unquestionable. This book will be an essential part of every mathematical library." (Viktor Ohanyan, zbMATH 1447.60004, 2020)