一种低错误平层LDPC码构造方法

发布时间：2018-11-25 17:29

【摘要】：针对低密度奇偶校验(low-density parity-check,LDPC)码在高信噪比区域可能存在错误平层的缺点,提出一种具有低错误平层LDPC码的新颖构造方法。在该方法中,基本矩阵由渐进边增长(progressive edge growth,PEG)算法搜索构造,通过在基本矩阵相应的Tanner图中增加校验节点,并将其与拥有最小额外信息度(extrinsic message degree,EMD)短环的变量节点相连来增大短环的连通性。另外,提出了一种基于伽罗华域的循环移位系数矩阵设计方案,无需计算机搜索即可完全避免4环的出现,降低算法复杂度。为了对该方法的可行性进行验证,分别对变量节点的度分布是规则和非规则的基本矩阵进行改进,在高斯白噪声(additive white gaussian noise,AWGN)信道下,采用置信传播(belief propagation,BP)迭代译码算法对改进后的码型进行仿真分析,仿真结果表明,利用该法所构造的码型可有效改善在高信噪比区域的错误平层。
[Abstract]:A novel construction method for low density parity check (low-density parity-check,LDPC) codes with low error level LDPC codes is proposed in this paper. In this method, the basic matrix is searched and constructed by the incremental edge-growing (progressive edge growth,PEG) algorithm. By adding the check node to the corresponding Tanner graph of the basic matrix, the basic matrix is matched with the (extrinsic message degree, with the minimum extra information degree. EMD) the variable nodes of the short ring are connected to increase the connectivity of the short ring. In addition, a design scheme of cyclic shift coefficient matrix based on Galois domain is proposed, which can completely avoid the emergence of four rings without computer search and reduce the complexity of the algorithm. In order to verify the feasibility of the method, the paper improves the basic matrix of variable nodes whose degree distribution is regular and irregular respectively. In Gao Si white noise (additive white gaussian noise,AWGN channel, confidence propagation (belief propagation, is adopted. BP) iterative decoding algorithm is used to simulate the improved code type. The simulation results show that the proposed algorithm can effectively improve the error level in the high SNR region.
【作者单位】：重庆邮电大学光通信与网络重点实验室;
【基金】：国家自然科学基金项目(61472464) 重庆市基础与前沿研究计划项目(cstc2015jcyj A0554) 2016年重庆邮电大学大学生科研训练计划项目(A2016-61)~~
【分类号】：TN911.22

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