基于寻找小重量码字算法的LDPC码开集识别

发布时间：2018-06-15 18:09

本文选题：信道编码识别 + LDPC码　；参考：《通信学报》2017年06期

【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]:The open set recognition of LDPC codes is a difficult problem in the field of channel coding recognition. Firstly, the number of received code vectors needed to realize open set recognition is analyzed, and the theoretical lower bound is given. Then, according to the lower bound, a new open set recognition method for LDPC codes is proposed based on the algorithm of finding small weight codewords. In this method, small weight vectors are searched one by one in the dual space of the received code vector space, that is, the sparse check vectors to be identified, so as to reconstruct the sparse check matrix. The exponential distribution is used to model the number of iterations, and the iterative stopping criterion and the computational complexity analysis of the method are given. Under the BER-free condition, the new method overcomes the limitations of the existing methods in the applicable range and the required data amount. Under the condition of error code, compared with the existing methods, it can improve the capability of anti-error and maintain lower computational complexity, which can meet the needs of practical applications. For QC-LDPC codes, the recognition performance can be significantly improved by using the quasi-cyclic property of its sparse check matrix.
【作者单位】：解放军信息工程大学信息系统工程学院;
【基金】：国家自然科学基金资助项目(No.61401511)~~
【分类号】：TN911.22

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