报告题目：Cooperative MIMO Relaying for 4G Broadband Wireless Networks
报告人：Prof. Benoit Champagne
Department of Electrical & Computer Engineering,
McGill University, Montréal, Canada
Abstract: Wireless relaying has been attracting much interest in recent years as a promising technique to overcome the impairments caused by multipath fading, shadowing and path loss in traditional communication systems. It is now being considered for coverage extension and capacity increase in high data rate wireless standards, including WiMAX (IEEE 802.16j) and 3GPP LTE-advanced. The introduction of multiple-input multiple-output (MIMO) techniques in the relaying framework, through the use of multiple antennas at the source, relay or destination, promises further leverage. The use of multiple relays is also well-suited to cooperative communications, which is emerging as a promising alternative to the traditional centralized communication-processing paradigm.
The talk will begin with a high-level introduction to wireless relaying within the framework of emerging technologies and standards for broadband wireless access. We will discuss important system level considerations, related standardization activities within the 802.16 and LTE-Advanced frameworks, and open research problems from a signal processing perspective. In the second part of the talk, we will present new hybrid strategies for MIMO relaying based on tandem combinations of different criteria for the backward and forward channels. This framework will be extended to cooperative MIMO relaying by generalization of a recently proposed cooperative MMSE structure. The performance of the various methods will be compared in terms of achievable ergodic capacity and bit error rates. In the last part of the talk, we will present some of our most recent work on adaptive beamforming for MIMO cooperative relaying. The new algorithms attempt to minimize the received interference power at the destination while preserving the desired source signal. The problem is reformulated as one of optimal state estimation and various adaptive solutions are developed via Kalman filtering techniques. Illustrative results will be presented to demonstrate the performance of these new adaptive solutions.
Bio: Benoit Champagne was born in Joliette (P.Q.) Canada. He received the B.Ing. degree in Engineering Physics from the Ecole Polytechnique de Montréal in 1983, the M.Sc. degree in Mathematical Physics from the Université de Montréal in 1985, and the Ph.D. degree in Electrical Engineering from the University of Toronto in 1990. From 1990 to 1999, he was an Assistant and then Associate Professor at INRS-Telecommunications, Université du Quebec, Montréal. In 1999, he joined McGill University, Montreal, where he is now a Full Professor within the Department of Electrical and Computer Engineering. He served as Associate Chair of Graduate Studies in the Department from 2004 to 2007.
Prof. Champagne’s research focuses on the development and investigation of new computational algorithms for the processing of information bearing signals by digital means. His interests span many areas of statistical signal processing, including detection and estimation, sensor array processing, adaptive filtering, and applications thereof to broadband communications. He has published several papers in these areas, including key works on time delay estimation, subspace tracking and spread sources localization. His research has been funded by the Natural Sciences and Engineering Research Council (NSERC) of Canada, the “Fonds de recherche sur la nature et les technologies” from the Government of Quebec, as well as some major industrial sponsors, including Nortel Networks, Bell Canada, InterDigital and Zarlink (now Microsemi). He has been an Associate Editor for the IEEE Signal Processing Letters and the EURASIP Journal on Applied Signal Processing and has served on the technical and organizing committees of several international conferences. He is currently Associate Editor for the IEEE Trans. on Signal Processing and a Senior Member of IEEE.