Symbol-Level Precoding: A New Paradigm For Physical-Layer Transmit Design
报告专家：利强
报告时间：2022年9月22日星期四晚上7：30-8：30
报告地点：腾讯会议：898-495-592
摘要：Symbol-level precoding (SLP) has recently emerged as a new paradigm for physical-layer transmit precoding in multiuser multi-input-multi-output (MIMO) channels. It exploits the underlying symbol constellation structure, which the conventional paradigm of linear precoding does not, to enhance symbol-level performance such as symbol error probability (SEP). In this talk, we will give a comprehensive study of SLP and establish the connection between linear precoding and SLP, identify the scenarios under which SLP is advantageous over linear precoding, and develop low-complexity SLP design schemes.
专家简介：Qiang Li received the B.Eng. and M.Phil. degrees in communication and information engineering from the University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2005 and 2008 respectively, and the Ph.D. degree in Electronic Engineering from The Chinese University of Hong Kong (CUHK), Hong Kong, in 2012. Since November 2013, he has been with the School of Information and Communication Engineering, UESTC, where he is currently a Professor. His research interests include signal processing and machine learning in wireless communications. He was the recipient of the First Prize Paper Award in the IEEE Signal Processing Society Postgraduate Forum Hong Kong Chapter in 2010, Best Paper Award of IEEE PIMRC 2016, and Best Paper Award of the IEEE SIGNAL PROCESSING LETTERS 2016 and Best Paper Award of CCEW 2022.
