"Efficient MIMO soft demodulation: a semidefinite relaxation approach" by Prof. Tim Davidson (Feb 11th, 11:00)
7 Fevereiro 2008, 12:39 - Pedro Flores Correia
Dept. Electrical and Computer Engineering,
Hamilton, Ontario, Canada
Wireless communication systems with multiple transmit and multiple receive antennas have the potential to provide data rates that are substantially higher than those of the single antenna systems. The core challenge in designing such multiple-input multiple-output (MIMO) systems is to achieve these rates with reasonable computational complexity. A standard transceiver architecture for moving towards that goal is MIMO bit-interleaved coded modulation with iterative (soft) demodulation and decoding (MIMO BICM-IDD). However, the computational cost of the (bit-wise) maximum a posteriori probability (MAP) soft demodulator increases exponentially with the number of bits transmitted per channel use, and hence there is considerable interest in the design of approximate (quasi-MAP) soft demodulation schemes with lower complexity.
In this talk we will develop a computationally-efficient and memory-efficient approach to quasi-MAP MIMO soft demodulation, based on semidefinite relaxation. Existing approaches to this problem either require storage of a large list of candidate bit-vectors, or the solution of multiple quadratic optimization problems with discrete-valued variables (each of which can be expensive to solve).
In contrast, the proposed demodulator does not require the storage of a candidate list, and involves the solution of a single (efficiently-solvable) semidefinite program per channel use. Our simulation results show that the resulting computational and memory efficiencies are obtained without incurring a significant degradation in performance. For ease of exposition the talk will focus on the case of QPSK signalling, but an extension to 16-QAM will be briefly described.
Although the focus of this talk is on a particular problem in communication systems, the proposed approach to that problem is based on some of the fundamental properties of semidefinite relaxation and the associated randomization algorithms. The talk will include an overview of these properties for the case of binary quadratic problems, and will also touch on some of the properties of semidefinite relaxation when applied to other problems. This material may be of interest to a broader audience.
The technical contribution of this talk is based on work with Mehran Nekuii at McMaster University, and Mikalai Kisialiou and Zhi-Quan (Tom) Luo at the University of Minnesota. (Mikalai is now with Intel, Portland, Orgeon.)
Tim Davidson received the B.Eng. (Hons. I) degree in Electronic Engineering from the University of Western Australia (UWA), Perth, in 1991 and the D.Phil. degree in Engineering Science from the University of Oxford, UK, in 1995.
He is currently an Associate Professor in the Department of Electrical and Computer Engineering at McMaster University, Hamilton, Ontario, Canada, where he holds the (Tier II) Canada Research Chair in Communication Systems, and is currently serving as Acting Director of the School of Computational Engineering and Science. His research interests lie in the general areas of communications, signal processing and control. He has held research positions at the Communications Research Laboratory at McMaster University, the Adaptive Signal Processing Laboratory at UWA, and the Australian Telecommunications Research Institute at Curtin University of Technology, Perth, Western Australia.
Dr. Davidson was awarded the 1991 J. A. Wood Memorial Prize (for "the most outstanding [UWA] graduand" in the pure and applied sciences) and the 1991 Rhodes Scholarship for Western Australia. He is currently serving as an Associate Editor of the IEEE Transactions on Signal Processing and as an Editor of the IEEE Transactions on Wireless Communications. He has also served as an Associate Editor of the IEEE Transactions on Circuits and Systems II, and as a Guest Co-editor of issues of the IEEE Journal on Selected Areas in Communications and the IEEE Journal on Selected Topics in Signal Processing.