LDPC code reconstruction based on algorithm of finding low weight code-words

Pei-dong YU; Hua PENG; Ke-xian GONG; Ze-liang CHEN

doi:10.11959/j.issn.1000-436x.2017116

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LDPC code reconstruction based on algorithm of finding low weight code-words

Papers | 更新时间：2024-06-05

- LDPC code reconstruction based on algorithm of finding low weight code-words
- Journal on Communications Vol. 38, Issue 6, Pages: 108-117(2017)
- 作者机构：
  
  解放军信息工程大学信息系统工程学院，河南郑州 450001
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61401511)
- DOI：10.11959/j.issn.1000-436x.2017116
  CLC： TN911.7
- Online First：2017-06，
  
  Published：25 June 2017
- 稿件说明：
移动端阅览
Pei-dong YU, Hua PENG, Ke-xian GONG, et al. LDPC code reconstruction based on algorithm of finding low weight code-words[J]. Journal on Communications, 2017, 38(6): 108-117.
DOI：

Pei-dong YU, Hua PENG, Ke-xian GONG, et al. LDPC code reconstruction based on algorithm of finding low weight code-words[J]. Journal on Communications, 2017, 38(6): 108-117. DOI： 10.11959/j.issn.1000-436x.2017116.

摘要

LDPC码的开集识别是信道编码识别领域的一个难点。首先，对实现开集识别所需接收码向量的数量进行了分析，给出了其理论下界。然后，根据这一下界，基于寻找小重量码字的算法，提出了一种新的LDPC码开集识别方法。该方法在接收码向量空间的对偶空间中逐个寻找小重量向量，即待识别的稀疏校验向量，从而重建稀疏校验矩阵。利用指数分布对迭代次数进行建模，给出了该方法的迭代停止准则及运算量分析。在无误码条件下，新方法克服了已有方法在适用范围和所需数据量的局限。在有误码条件下，与已有方法相比，在提高抗误码能力的同时保持较低的运算复杂度，更能满足实际应用的需求。对于QC-LDPC码，利用其稀疏校验矩阵的准循环特性，可以显著提高识别性能。

Abstract

LDPC code reconstruction without a candidate set is one of the tough problems in channel code reconstruction.First

theoretical analysis was provided for the number of received code-vectors needed for the reconstruction

and a lower bound was derived.Then

according to the lower bound

and based on an algorithm for finding low weight code-words

a new reconstruction method was proposed.It looked for low weight vectors one by one from the dual space of the received code-vector space and used them to reconstruct the sparse parity-check matrices.Number of iterations and the computational complexity of the method were analyzed based on exponential distribution theory.Under noise-free conditions

drawbacks of the existing method

including limited applicable range and large quantity of required data

have been overcame.Under noisy conditions

the proposed method has higher robustness against noise and relatively low complexity

compared to existing methods.For QC-LDPC codes

the reconstruction performance can be further improved using the quasi-cyclic property of their sparse parity-check matrices.

关键词

Keywords

references

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