Variable non-uniform quantized belief propagation algorithm for LDPC decoding

Abstract

Non-uniform quantization for messages in Low-Density Parity-Check (LDPC) decoding can reduce implementation complexity and mitigate performance loss. But the distribution of messages varies in the iterative decoding. This letter proposes a variable non-uniform quantized Belief Propagation (BP) algorithm. The BP decoding is analyzed by density evolution with Gaussian approximation. Since the probability density of messages can be well approximated by Gaussian distribution, by the unbiased estimation of variance, the distribution of messages can be tracked during the iteration. Thus the non-uniform quantization scheme can be optimized to minimize the distortion. Simulation results show that the variable non-uniform quantization scheme can achieve better error rate performance and faster decoding convergence than the conventional non-uniform quantization and uniform quantization schemes.