2013.07.01应通信系王昕教授的邀请，香港中文大学的袁晓军教授来我校访问，并做学术报告。时间是7月1日上午10:30-11:30，地点是计算中心楼B415会议室，附件是报告人的简历和报告摘要。欢迎感兴趣的老师和学生参加！
　　　Prof. Xiaojun Yuan
　　　Research Assistant Professor
　　　Institute of Network Coding
　　　Department of Information Engineering
      Xiaojun Yuan received the B.S. degree in electronic and information systems from Shanghai Jiaotong University, the M.S. degree in circuit and systems from Fudan University, and the Ph.D. degree in electrical engineering from City University of Hong Kong in 2008. After graduation, he was a research fellow at the Department of Electronic Engineering, City University of Hong Kong. During 2009-2010, he was also working as a visiting scholar at the University of Hawaii at Manoa. He is now a research assistant professor at the Institute of Network Coding, Department of Information Engineering, The Chinese University of Hong Kong. His research interest falls into the general area of signal processing and information theory, including channel coding and coded modulation, massive multiple-input multiple-output (MIMO) communications, physical-layer network coding (PNC), etc. He has published over 40 refereed papers in the leading journals and conferences in the related areas. He served as the Technical Program Committee (TPC) members for several international conferences including ICC, WCNC, PIMRC, etc.
      Title: DFT-Spread MIMO Systems: Iterative Equalization, Evolution Analysis, and Precoder Optimization
      Abstract: We develop a novel belief-propagation (BP) based iterative equalization algorithm for discrete-Fourier-transform (DFT) spread multiple-input multiple-output (MIMO) systems. An evolution technique, referred to as signal-to-interference-plus-noise-ratio (SINR) variance transfer chart, is established to accurately characterize the behavior of the proposed equalizer. We show that the proposed scheme significantly outperforms the existing non-linear MIMO equalizers in various system setups. We further investigate the precoder design based on the newly developed evolution technique, under the assumption of both full and partial channel state information at the transmitter (CSIT). We derive the optimal precoding directions, and show that the precoder optimization then boils down to a simple power allocation problem that is solvable using convex programming. Numerical results demonstrate that the optimized precoder can achieve a significant power gain, as compared with the non-optimized scheme.