Sparse Signal Processing for Massive MIMO Communications

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.

Autorentext

Zhen Gao received the B.S. degree in information engineering from Beijing Institute of Technology, Beijing, China, in 2011 and the Ph.D. degree in communication and signal processing from Tsinghua National Laboratory for Information Science and Technology, Department of Electronic Engineering, Tsinghua University, China, in 2016. He is currently Assistant Professor at Beijing Institute of Technology. His research interests are in wireless communications, with a focus on multi-carrier modulations, multiple antenna systems, and sparse signal processing. He was a recipient of the IEEE Broadcast Technology Society 2016 Scott Helt Memorial Award (Best Paper), the Exemplary Reviewer of IEEE COMMUNICATIONS LETTERS in 2016, the IET ELECTRONICS LETTERS Premium Award (Best Paper) 2016, the Young Elite Scientists Sponsorship Program (2018-2020) from China Association for Science and Technology, the Elsevier China Highly Cited Scholar (2020), and the First Prize of Natural Science granted by Chinese Institute of Electronics.