Title: How to Run Your LDPC Decoders Faster？

        讲座时间：5月16日下午4：00

讲座地点：海韵行政楼C座505报告厅

Speaker: Prof. Francis Lau

Affiliation: Department of Electronic and Information Engineering, The Hong Kong Polytechnic University 

Abstract

Low-density parity-check (LDPC) codes are very powerful error-correction codes with capability approaching the Shannon's limits. In evaluating the error performance of a LDPC code, the computer simulation time taken becomes a primary concern when tens of millions of noise-corrupted codewords are to be decoded, particularly for codes with very long lengths. In this presentation, we show two general approaches to speed up the simulations of the LDPC decoder. The first approach is based on compressing the parity-check matrix of a LDPC code in the check-node domain (CND) and in the bit-node domain (BND). In the second method, we run the simulations using General Purpose Graphics Processing Units (GPGPUs). We illustrate with some real examples that both methods show substantial improvements in terms of simulation time.

About the speaker

Prof. Francis Lau received the BEng degree and the PhD degree in electrical and electronic engineering from King's College London, University of London, UK, in 1989 and 1993, respectively. He is currently a Professor and Associate Head at the Department of Electronic and Information Engineering, The Hong Kong Polytechnic University. He has co-authored 3 monographs and more than 200 research publications. He is also a co-holder of two US patents and one pending US patent. He served as an associate editor for IEEE Transactions on Circuits and Systems Part I, IEEE Transactions on Circuits and Systems Part II, Dynamics of Continuous, Discrete and Impulsive Systems, Series B and was a co-guest editor of Circuits, Systems and Signal Processing. Currently, he is serving as a guest associate editor of International Journal of Bifurcations and Chaos, and as an associate editor of IEICE Transactions (Special Section on Recent Progress in Nonlinear Theory and Its Applications).

His main research interests include channel coding, cooperative communication networks, chaos-based digital communications, application of complex-network theories, and wireless sensor networks.