Department of Electronic and Computer Engineering Seminar - Reconfigurable Intelligent Surface Aided MIMO Communications: Challenges and Opportunities
Reconfigurable intelligent surface (RIS) is regarded as one of the candidate technologies to enable next-generation wireless communications (6G). A RIS is made of a large number of low-cost reconfigurable elements, a.k.a. meta-atoms or unit cells, that are able to control how incident electromagnetic (EM) waves are reflected. The unit cells of a RIS can be designed to cooperatively achieve specific purposes, such as scattering the impinging waves, absorbing the impinging waves, and focusing the reflected wave to certain directions. In this talk, we introduce the channel modeling, optimization, and capacity analysis of RIS-assisted MIMO systems. First of all, we propose a partition-based passive beamforming method to reduce the number of variables to be optimized, thereby reducing computational overhead. Then, we propose a near-field RIS-assisted MIMO channel model based on the spherical-wave assumption. Based on the established channel model, we study the spatial multiplexing capability of the cascaded line-of-sight MIMO channel, and analyze the capacity of the system by jointly optimizing the active and passive beamforming, and the transceiver array orientations.
Xiaojun Yuan received the Ph.D. degree in electrical engineering from the City University of Hong Kong in 2009. From 2009 to 2011, he was a Research Fellow at the Department of Electronic Engineering, City University of Hong Kong. He was also a Visiting Scholar at the Department of Electrical Engineering, University of Hawaii at Manoa, in Spring and Summer 2009 and Spring and Summer 2010. From 2011 to 2014, he was a Research Assistant Professor with the Institute of Network Coding, The Chinese University of Hong Kong. From 2014 to 2017, he was an Assistant Professor with the School of Information Science and Technology, ShanghaiTech University. He is currently a State-Specially-Recruited Professor with the University of Electronic Science and Technology of China. His research interests include signal processing, machine learning, and wireless communications, including but not limited to intelligent communications, structured signal reconstruction, Bayesian approximate inference, and distributed learning. He has published over 200 peer-reviewed research papers in the leading international journals and conferences in the related areas. He has served on several technical programs for international conferences. He was a co-recipient of the IEEE Heinrich Hertz Award for Best Communication Letter in 2022. He was an Editor of a number of IEEE leading journals, including IEEE Transactions on Wireless Communications and IEEE Transactions on Communications.