LDPC Decoder Based on Markov Chain Monte Carlo Method

摘要

Low-density parity check (LDPC) codes have attracted the attention of a large number of researchers with its near-Shannon performance and easy implementation features. As a data coding scheme under the 5G scenario, how to achieve efficient encoding/decoding for LDPC codes has become one of the important research topics. Under this condition, this paper 1) proposes a novel decoding algorithm for LDPC codes using the Markov Chain Monte Carlo (MCMC) method and 2) introduces two improved versions, MCMC-S and MCMC-L, which achieve better results. Simulation figures show that the improved methods outperform the traditional belief propagation (BP) decoding method in relatively short codes by more than 1 dB at the bit error rate (BER) of 10^{-3. Very large scale integration (VLSI) architecture of the proposed method is also given in this paper.}