Title: From Bayesian Statistics to Large-Scale MIMO Communications
时间：2024.11.14 星期四 15:00-17:00
地点：无线谷1208会议室
Abstract: Large-scale MIMO systems have emerged as a cornerstone for next-generation wireless communication networks. While extended research has been conducted on signal processing and transceiver design in these systems, the fundamental Shannon capacity limit remains elusive in many settings, particularly in the presence of system non-linearities. In this talk, we explore the connection between statistics and communication, and introduce a novel approach that leverages information-theoretic asymptotics from Bayesian statistics to derive the Shannon capacity of such systems. We reveal the critical role of the Fisher information and Jeffreys' prior in this characterization, and demonstrate how to apply this method to derive the asymptotic capacity of various channel models. Examples include the MIMO channels with 1-bit ADC, phase noise, and imperfect channel state information.
Bio: Sheng Yang received the B.E. degree in electrical engineering from Jiaotong University, Shanghai, China, in 2001, and both the engineer degree and the M.Sc. degree in electrical engineering from Telecom Paris, France, in 2004, respectively. In 2007, he obtained his Ph.D. from Université de Pierre et Marie Curie (Paris VI). From October 2007 to November 2008, he was with Motorola Research Center in Gif-sur-Yvette, France, as a senior staff research engineer. Since December 2008, he has joined CentraleSupélec, Paris-Saclay University, where he is currently a full professor. He has also hold visiting professorships in the University of Hong Kong (2015, 2016) and the Hong Kong University of Science and Technology (2023, 2024). He received the 2015 IEEE ComSoc Young Researcher Award for the Europe, Middle East, and Africa Region (EMEA). He was an associate editor of the IEEE transactions on wireless communications from 2015 to 2020. He is currently an associate editor of the IEEE transactions on information theory.
