This book focuses on the design of low-complexity iterative receivers in high spectral efficiency communication systems, especially under frequency-selective fading channels. Specifically, it combines multi-carrier faster-than-Nyquist (MFTN) signaling, spectrally efficient frequency division multiplexing (SEFDM), and index modulation (IM) to study the hybrid message passing based low-complexity iterative receivers, the frequency-domain joint channel estimation and equalization (FDJCEE) algorithm, and the vector approximate message passing (VAMP) based iterative equalization algorithms. These methods effectively address the challenges of symbol detection and channel estimation for MFTN signaling and significantly improve the spectral efficiency and bit error rate (BER) performance. This book is of a good reference for researchers, engineers, and students in the fields of wireless communications and signal processing.
Nan Wu received the B.S., M.S., and Ph.D. degrees from the Beijing Institute of Technology (BIT), Beijing, China, in 2003, 2005, and 2011, respectively. From 2008 to 2009, he was a Visiting Ph.D. Student with the Department of Electrical Engineering, Pennsylvania State University, USA. He is currently a Professor with the School of Information and Electronics, BIT. His research interests include signal processing in wireless communication networks. He was a recipient of the National Excellent Doctoral Dissertation Award by MOE of China in 2013. He serves as an Editorial Board Member for the IEEE Wireless Communications Letters.
Yunsi Ma received the B.S. degree from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2013, the M.S. degree from China Academy of Space Technology, Beijing, China, in 2016, the Ph.D. degree from China Academy of Space Technology, Beijing, China, in 2022, and the Ph.D. degree from the University of Technology Sydney, Sydney, Australia, in 2023. She is currently a senior engineer with Huawei Technologies Co., Ltd., Shanghai, China. Her research interests include signal processing of faster-than-Nyquist signaling, statistical inference on graphical models and its application to wireless communications, and short-distance wireless commnunication standards.
Rongkun Jiang received the B.S. and Ph.D. degrees from the School of Information and Electronics, Beijing Institute of Technology (BIT), Beijing, China, in 2012 and 2020, respectively. He was a Postdoctoral Researcher of Information and Communication Engineering with BIT from 2020 to 2023, where he is currently a Research Assistant with the School of Integrated Circuits and Electronics. His research interests include wireless commnunication, RIS, ISAC, and AI-based solutions for signal processing. He was a recipient of the Best Paper Award from IEICE, Japan in 2020 and has been recognized as an Exemplary Reviewer of IEEE Wireless Communications Letters.
