Introduction -- Massive MIMO Performance Analysis and Channel Estimation Scheme in Sparse Channels -- Channel Estimation Based on Structured Compressed Sensing Theory in FDD Massive MIMO Systems -- Channel Feedback Based on Distributed Compressed Sensing Theory in FDD Massive MIMO Systems -- Channel Estimation and Beamforming Based on Compressed Sensing Theory in mmWave Massive MIMO Systems -- Sparse Channel Estimation Based on Spectral Estimation Theory for mmWave Massive MIMO Systems -- Quasi-Optimal Signals Detection for Massive Spatial Modulation MIMO Systems Based on Structured Compressed Sensing -- Multiuser Signal Detection Based on Compressed Sensing for Massive Media Modulation MIMO Systems -- Compressed Sensing Mass Access Techniques in Medium Modulation Assisted IoT Machine Type Communication -- Time-varying Channel Estimation Based on Compressed Sensing Theory for TDS-OFDM Systems -- Summary and Prospects for Massive MIMOTechnology.

The book focuses on utilizing sparse signal processing techniques in designing massive MIMO communication systems. As the number of antennas has been increasing rapidly for years, extremely high-dimensional channel matrix and massive user access urge for algorithms with much higher efficiency. This book provides in-depth discussions on compressive sensing techniques and simulates the performance on wireless systems. The easy-to-understand instructions with detailed simulations and open-sourced codes provide convenience for readers such as researchers, engineers, and graduate students in the fields of wireless communications.