Topic：Beamforming Games with Quantized CSI in Two-user Interference Channels Time：2016年6月21日（周二）下午15:30-16:30 Venue：信电大楼-215学术厅 Speaker：Huaiyu Dai, Associated Professor                    Electrical and Computer Engineering                    North Carolina State University ，USA

Biography：

Huaiyu Dai (M’03, SM’09) received the B.E. and M.S. degrees in electrical engineering from Tsinghua University, Beijing, China, in 1996 and 1998, respectively, and the Ph.D. degree in electrical engineering from Princeton University, Princeton, NJ in 2002.

He was with Bell Labs, Lucent Technologies, Holmdel, NJ, during summer 2000, and with AT&T Labs-Research, Middletown, NJ, during summer 2001. Currently he is a Professor of Electrical and Computer Engineering at NC State University, Raleigh. His research interests are in the general areas of communication systems and networks, advanced signal processing for digital communications, and communication theory and information theory. His current research focuses on networked information processing and crosslayer design in wireless networks, cognitive radio networks, wireless security, and associated information-theoretic and computation-theoretic analysis. 

He has served as an editor of IEEE Transactions on Communications, Signal Processing, and Wireless Communications. Currently he is an Area Editor in charge of wireless communications for IEEE Transactions on Communications. He co-edited two special issues of EURASIP journals on distributed signal processing techniques for wireless sensor networks, and on multiuser information theory and related applications, respectively. He co-chairs the Signal Processing for Communications Symposium of IEEE Globecom 2013, the Communications Theory Symposium of IEEE ICC 2014, and the Wireless Communications Symposium of IEEE Globecom 2014.

Abstract：

In this work, we consider a beamforming game of the transmitters in a two-user multiple-input single-output interference channel using limited feedback and investigate how each transmitter should find a strategy from the quantized channel state information (CSI). In the beamforming game, each transmitter (a player) tries to maximize the achievable rate (a payoff function) via a proper beamforming strategy. In our case, each transmitter’s beamforming strategy is represented by a linear combining factor between the maximum-ratio transmission (MRT) and the zero-forcing (ZF) beamforming vectors, which is shown to be a Pareto optimal achieving strategy. With the perfect CSI, each transmitter can know the exact achievable rate region, and hence can find the beamforming strategy corresponding to any point in the achievable rate region. With limited feedback, however, the transmitters can only conjecture the achievable rate region from the quantized CSI, so their optimal strategies may not be optimal anymore. Considering the quantized CSI at the transmitter, we first find the Nash equilibrium in a noncooperative game. Then, in a cooperative (Nash bargaining) game, we find a Nash bargaining solution and test its validity. Finally, we propose three bargaining solutions that improve the validity of the cooperation or the average Nash product. Our proposed bargaining solutions utilize the codebook structure; instead of each quantized channel itself, its Voronoi region is considered.