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.