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ICC
2009
IEEE

Low Complexity Markov Chain Monte Carlo Detector for Channels with Intersymbol Interference

9 years 5 months ago
Low Complexity Markov Chain Monte Carlo Detector for Channels with Intersymbol Interference
— In this paper, we propose a novel low complexity soft-in soft-out (SISO) equalizer using the Markov chain Monte Carlo (MCMC) technique. Direct application of MCMC to SISO equalization (reported in a previous work) results in a sequential processing algorithm that leads to a long processing delay in the communication link. Using the tool of factor graph, we propose a novel parallel processing algorithm that reduces the processing delay by orders of magnitude. Numerical results show that, both the sequential and parallel processing SISO equalizers perform similarly well and achieve a performance that is only slightly worse than the optimum SISO equalizer. The optimum SISO equalizer, on the other hand, has a complexity that grows exponentially with the size of the memory of the channel, while the complexity of the proposed SISO equalizers grows linearly.
Ronghui Peng, Rong-Rong Chen, Behrouz Farhang-Boro
Added 21 May 2010
Updated 21 May 2010
Type Conference
Year 2009
Where ICC
Authors Ronghui Peng, Rong-Rong Chen, Behrouz Farhang-Boroujeny
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