一种加速收敛的LDPC码译码算法

Fast Convergence Decoding Scheme for LDPC Codes

对高斯信道下LDPC(Low-Density Parity-Check)码的传统的译码算法进行分析,指出影响收敛速度的原因,并提出了一种基于整数运算的加速收敛的LDPC码译码算法。该算法融合分层译码(Layered Belief Propagation)算法、带偏移量的最小和算法(Offset Min-Sum)以及量化的优势。仿真验证表明该算法有效地减少了译码复杂度,加速了译码收敛,且性能上同传统的量化最小和算法相比没有下降。

We consider the convergence problem of the conventional decoding scheme of Low-Density Parity-Check（LDPC） codes over Additive White Gaussian Noise（AWGN） channels.In this correspondence,we propose a fast convergence decoding scheme based on quantization,which is a comprehensive method of taking advantage of the Layered Belief Propagation（LBP） algorithm,the Offset Min-Sum（OMS） algorithm and the quantization method.Compared to the conventional quantized Min-Sum algorithm,the proposed scheme efficiently reduces the decoding complexity and significantly accelerates the decoding convergence with no additional performance loss.We show that with simulations.