Applications of Machine Learning in Wireless Communications

Ruisi He is a Professor at the State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, China. His research interests include measurement and modelling of wireless channels, machine learning and clustering analysis in wireless communications, vehicular and high-speed railway communications, 5G massive MIMO and high frequency communication techniques. Zhiguo Ding is a Professor at the School of Electrical and Electronic Engineering at the University of Manchester, UK. He holds a Ph. D degree in Electrical Engineering from Imperial College London, UK. His research interests are in 5G networks, game theory, cooperative and energy harvesting networks and statistical signal processing.

Chapter 1: Introduction of machine learning
Chapter 2: Machine-learning-enabled channel modeling
Chapter 3: Channel prediction based on machine-learning algorithms
Chapter 4: Machine-learning-based channel estimation
Chapter 5: Signal identification in cognitive radios using machine learning
Chapter 6: Compressive sensing for wireless sensor networks
Chapter 7: Reinforcement learning-based channel sharing in wireless vehicular networks
Chapter 8: Machine-learning-based perceptual video coding in wireless multimedia communications
Chapter 9: Machine-learning-based saliency detection and its video decoding application in wireless multimedia communications
Chapter 10: Deep learning for indoor localization based on bimodal CSI data
Chapter 11: Reinforcement-learning-based wireless resource allocation
Chapter 12: Q-learning-based power control in small-cell networks
Chapter 13: Data-driven vehicular mobility modeling and prediction