报告题目：Achievable Rates and Training Optimization for Uplink Multiuser Massive MIMO Systems
报 告 人：王正道教授
时间：2016年6月13日下午2:30
地点：安徽大学磬苑校区理工B楼303
主办单位：电子信息工程学院
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科学技术处
2016年6月12日
报告人简介：
Zhengdao Wang received his Bachelor's degree in Electronic Engineering and Information Science from the University of Science and Technology of China (USTC), 1996, the Master's degree in Electrical and Computer Engineering from the University of Virginia, 1999, and Ph.D. in Electrical and Computer Engineering from the University of Minnesota, 2002. He is now a professor with the Department of Electrical and Computer Engineering at the IowaStateUniversity. His interests are in the areas of signal processing, communications, and information theory. He served as an associate editor for IEEE Transactions on Vehicular Technology from April 2004 to April 2006, an Associate Editor for IEEE Signal Processing Letters between August 2005 and August 2008, and an Associate Editor for IEEE Transactions on Signal Processing between 2013 and 2015. He was a co-recipient of the IEEE Signal Processing Magazine Best Paper Award in 2003 and the IEEE Communications Society Marconi Paper Prize Award in 2004, and the EURASIP Journal on Advances in Signal Processing Best Paper Award, in 2009. He is currently serving as an Editor for The IEEE Signal Processing Society Online Video Library, and an Associate Editor for IEEE Transactions on Wireless Communications. He is an IEEE Fellow.
报告简介：We study the performance of uplink transmission in a large-scale (massive) MIMO system, where all the transmitters have single antennas and the receiver (base station) has a large number of antennas. Specifically, we first derive the rates that are possible through minimum mean-squared error (MMSE) channel estimation and three linear receivers: maximum ratio combining (MRC), zero-forcing (ZF), and MMSE. Based on the derived rates, we quantify the amount of energy savings that are possible through increased number of base-station antennas or increased coherence interval. We also analyze achievable total degrees of freedom (DoF) of such a system without assuming channel state information at the receiver, which is shown to be the same as that of a point-to-point MIMO channel. Linear receiver is sufficient to achieve total DoF when the number of users is less than the number of antennas. Otherwise, nonlinear processing is necessary to achieve the full degrees of freedom. Finally, the training period and optimal training energy allocation under the average and peak power constraints are optimized jointly to maximize the achievable sum rate when either MRC or ZF receiver is adopted at the receiver.