电子学报 ›› 2018, Vol. 46 ›› Issue (3): 652-658.DOI: 10.3969/j.issn.0372-2112.2018.03.021

• 学术论文 • 上一篇    下一篇

误码条件下LDPC码参数的盲估计

陈泽亮, 彭华, 巩克现, 于沛东, 王伟年   

  1. 信息工程大学信息系统工程学院, 河南郑州 450002
  • 收稿日期:2016-11-23 修回日期:2017-04-03 出版日期:2018-03-25
    • 作者简介:
    • 陈泽亮,男,1992年4月出生于湖南岳阳.信息工程大学硕士生,主要研究方向为信道编码识别分析.E-mail:zelchen@163.com;彭华,男,1973年8月出生于江西萍乡.信息工程大学教授、博士生导师,主要研究方向为软件无线电、通信信号处理等.E-mail:Peng_Hua@163.com
    • 基金资助:
    • 国家自然科学基金 (No.61401511)

A Method for Blind Recognition of LDPC Codes in a Noisy Environment

CHEN Ze-liang, PENG Hua, GONG Ke-xian, YU Pei-dong, WANG Wei-nian   

  1. Information Engineering University, Zhengzhou, Henan 450002, China
  • Received:2016-11-23 Revised:2017-04-03 Online:2018-03-25 Published:2018-03-25
    • Supported by:
    • National Natural Science Foundation of China (No.61401511)

摘要: 针对非合作信号处理中LDPC码(Low-Density Parity-Check)的盲识别问题,提出了一种容错能力较强的开集识别算法.该算法通过对码字矩阵进行高斯约旦消元找到汉明重量较小的"相关列",并根据"相关列"中所包含的约束关系求得LDPC码的校验向量,然后剔除"相关列"中为"1"位置对应的错误码字.若根据高斯约旦消元求校验向量和剔除错误码字进行迭代无法得到更多校验向量,则对得到的这些校验向量进行稀疏化,再进行译码纠错.最后,综合利用校验向量的求解,错误码字的剔除,校验向量稀疏化,LDPC码译码进行迭代,实现LDPC码校验矩阵的有效重建.仿真结果表明,对于IEEE 802.16e标准中的(576,288)LDPC码,在误比特率为0.0022时,本文算法仍可以达到较好的识别效果.

关键词: 信道编码, LDPC码, 盲识别, 校验向量, 稀疏化, 开集识别, 误比特率

Abstract:

A strong fault tolerance algorithm was proposed for LDPC (Low-Density Parity-Check) code reconstruction without a candidate set in a non-cooperative context. The algorithm uses Gauss Jordan elimination to find related columns with low Hamming weight and obtains the parity-check vector of LDPC codes according to the constraint relationship contained in the related column. Then the error code corresponding to the "1" position in the related column is removed. If the iteration according to Gauss Jordan elimination and the removing of error code can not get more parity-check vectors, then it makes these resulting parity-check vectors to be sparse and uses the sparse vectors to error correction. Finally, it reconstructs LDPC parity-check matrix effectively by making comprehensive use of parity-check vector solution, error code elimination, parity-check matrix sparsity and LDPC codes decoding to iterate. Simulation results show that, for the (576, 288) LDPC codes in IEEE 802. 16e standard, the proposed algorithm can provide good performance even when the bit error rate is 0. 0022.

Key words: channel coding, LDPC codes, blind recognition, parity-check vector, sparse, open set recognition, bit error rate

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