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Design and Optimization for 5G Wireless Communications
Haesik Kim (Author)
9781119494553, Wiley
Hardback, published 16 April 2020
424 pages
24.6 x 17.5 x 2.8 cm, 0.885 kg
This book offers a technical background to the design and optimization of wireless communication systems, covering optimization algorithms for wireless and 5G communication systems design. The book introduces the design and optimization systems which target capacity, latency, and connection density; including Enhanced Mobile Broadband Communication (eMBB), Ultra-Reliable and Low Latency Communication (URLL), and Massive Machine Type Communication (mMTC). The book is organized into two distinct parts: Part I, mathematical methods and optimization algorithms for wireless communications are introduced, providing the reader with the required mathematical background. In Part II, 5G communication systems are designed and optimized using the mathematical methods and optimization algorithms.
Preface xi Part I Mathematical Methods and Optimization Theories for Wireless Communications 1 1 Historical Sketch of Cellular Communications and Networks 3 2 5G Wireless Communication System Parameters and Requirements 13 3 Mathematical Methods for Wireless Communications 21 4 Mathematical Optimization Techniques for Wireless Communications 97 5 Machine Learning 151 Part II Design and Optimization for 5G Wireless Communications and Networks 195 6 Design Principles for 5G Communications and Networks 197 7 Enhanced Mobile Broadband Communication Systems 239 8 Ultra-Reliable and Low Latency Communication Systems 303 9 Massive Machine Type Communication Systems 343 Problems 392
List of Abbreviations xiii
1.1 Evolution of Cellular Communications and Networks 3
1.2 Evolution to 5G Networks 9
2.1 5G Requirements 13
2.2 Trade-off of 5G System Metrics 16
3.1 Signal Spaces 21
3.2 Approximation and Estimation in Signal Spaces 32
3.3 Matrix Factorization 71
4.1 Introduction 97
4.2 Mathematical Modeling and Optimization Process 99
4.3 Linear Programming 108
4.4 Convex Optimization 120
4.5 Gradient Descent Method 138
5.1 Artificial Intelligence, Machine Learning, and Deep Learning 152
5.2 Supervised and Unsupervised Learning 153
5.3 Reinforcement Learning 177
6.1 New Design Approaches and Key Challenges of 5G Communications and Networks 198
6.2 5G New Radio 207
6.3 5G Key Enabling Techniques 226
7.1 Introduction 239
7.2 Design Approaches of eMBB Systems 240
7.3 MIMO 242
7.4 5G Multiple Access Techniques 271
7.5 5G Channel Coding and Modulation 284
8.1 Design Approaches of URLLC Systems 304
8.2 Short Packet Transmission 306
8.3 Latency Analysis 317
8.4 Multi-Access Edge Computing 328
9.1 Introduction 343
9.2 Design Approaches of mMTC Systems 344
9.3 Robust Optimization 351
9.4 Power Control and Management 362
9.5 Wireless Sensor Networks 376
References 393
Index 397
Subject Areas: Mathematics [PB]
