低密度奇偶校验码的低复杂度迭代译码算法

Low-complexity iterative decoding algorithm for low-density parity-check codes

迭代大数逻辑(iterative majority-logic decoding,IMLGD)译码算法是低密度奇偶校验(low-density parity-check,LDPC)码的一类重要的迭代译码算法。相对LDPC码基于置信传播准则的译码算法,IMLGD译码算法的复杂度有所降低,但是性能有所下降。针对这一问题,提出了一种修正迭代大数逻辑译码算法(modified iterative majority-logic decoding,MIMLGD)。该算法利用校验方程的置信度对译码迭代过程中的各比特外信息进行修正。仿真结果表明,提出的MIMLGD译码算法相对于原始迭代大数逻辑译码算法在同样信噪比下具有更低的误比特率。此外,该算法保持了IMLGD译码算法的低复杂度特征,并且避免了对于特定的码搜索修正因子的过程,具有良好的通用性,是实际应用的良好选择。

Iterative majority-logic decoding(IMLGD)algorithm is a kind of important iterative decoding algorithm of low-density parity-check(LDPC)codes.Compared with the decoding methods of LDPC code based on the belief propagation principles,the complexity of IMLGD algorithm is reduced by a little at the expense of a little of performance degradation.In order to tackle the problem,a modified iterative majority-logic decoding(MIMLGD)algorithm is proposed in the paper.The algorithm uses the confidence degree of check equation to modify the extrinsic information of bit nodes appearing in the decoding iteration process.Simulation results show that the proposed MIMLGD algorithm has a lower bit error rate than the conventional IMLGD algorithm at a given signal-to-noise ratio.The low-complexity property of the IMLGD algorithm is maintained for the proposed MIMLGD algorithm.Moreover,the proposed algorithm keeps the feature of low-complexity of iterative majority-logic decoding algorithm,in addition,it avoids the process of searching correction factor and has excellent universality,it is a sound selection in practical application.