引入混洗策略和改进变量节点更新的最小和译码算法

Min-Sum Decoding Algorithm that Introduced Shuffled Strategy and Improved Variable Node Update

低密度奇偶校验码属于一种线性的分组码,近年来得到了很大的关注。目前被广泛应用的最小和(MS)算法译码损失较多,而且该算法属于洪泛调度,译码收敛速度较慢。为此提出了引入混洗策略和改进变量节点更新的MS(shuffled-VNU-MS)译码算法,该改进算法在本次迭代中更新某列校验节点信息时,可以利用到前序列最新的变量节点信息,且变量节点信息是通过加权因子平均后的信息。仿真结果表明:当码长为256,码率为0.5,误码率为10-5时,本文改进的译码算法shuffled-VNU-MS相比MS算法,编码增益提高了约0.92 dB。当信噪比为0时,本文改进算法译码收敛速度相比MS算法提高了约52%。

Lowdensity paritycheck code is a kind of linear block code,which has received much attention in recent years.At present,the minsum(MS)algorithm,which is widely used,has a lot of decoding loss,and it belongs to flood scheduling,so the decoding convergence speed is slow.In this paper,the MS decoding algorithm that introduced shuffled strategy and improved variable node update(shuffledVNUMS)is proposed.When the improved algorithm updates check node information of current column in this iteration,it can use the latest variable node information of the previous sequence,and the variable node information is averaged by the weighted factor.The simulation results show that when the code length is 256,the code rate is 0.5,and the bit error rate is 10-5,shuffledVNUMS algorithm increases the coding gain by about 0.92 dB compared with the MS algorithm.When the signal to noise ratio is 0,compared with the MS algorithm,shuffledVNUMS algorithm can improve the decoding convergence speed by about 52%.