高误码率下基于随机抽取的LDPC码校验矩阵重建

doi:10.11959/j.issn.1000-436x.2023062

通信学报 ›› 2023, Vol. 44 ›› Issue (3): 128-137.doi: 10.11959/j.issn.1000-436x.2023062

高误码率下基于随机抽取的LDPC码校验矩阵重建

王忠勇¹, 李正豪¹, 巩克现¹, 孙鹏¹, 李清涛²

¹ 郑州大学电气与信息工程学院，河南郑州 450001
² 61818部队，湖北武汉 430000

修回日期:2023-01-31 出版日期:2023-03-25 发布日期:2023-03-01
作者简介:王忠勇（1965- ），男，江西遂川人，博士，郑州大学教授、博士生导师，主要研究方向为通信信号处理、嵌入式系统等
李正豪（1999- ），男，河南禹州人，郑州大学硕士生，主要研究方向为信道编码识别分析
巩克现（1976- ），男，山东泰安人，博士，郑州大学教授、博士生导师，主要研究方向为无线通信信号分析与处理、信道编码、无线接入、目标监测及电子对抗等
孙鹏（1990- ），男，河南周口人，博士，郑州大学讲师，主要研究方向为无线通信、消息传递理论、毫米波通信
李清涛（1976- ），男，河南唐河人，61818部队高级工程师，主要研究方向为信号与信息处理
基金资助:
国家自然科学基金资助项目(61901417);河南省科技攻关基金资助项目(212102210173);河南省科技攻关基金资助项目(212102210566);国家重点研发计划基金资助项目(2019QY0302)

Reconstruction of LDPC code check matrix based on random extraction at high bit error rate

Zhongyong WANG¹, Zhenghao LI¹, Kexian GONG¹, Peng SUN¹, Qingtao LI²

¹ School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China
² 61818 Forces, Wuhan 430000, China

Revised:2023-01-31 Online:2023-03-25 Published:2023-03-01
Supported by:
The National Natural Science Foundation of China(61901417);Henan Science and Technology Research Project(212102210173);Henan Science and Technology Research Project(212102210566);The National Key Research and Development Program of China(2019QY0302)

摘要/Abstract

摘要：

为改善高误码率下LDPC码稀疏校验矩阵重建算法的性能，提出了接收码字个数充足和不充足条件下容错能力较强的校验矩阵开集识别算法。首先，通过多次随机抽取码字的部分比特构建新的码字空间，在较低维度下利用高斯消元法求解对偶向量并还原出校验向量；其次，利用该校验向量，采用“剔除错误码字”或“翻转最低不可靠位”的方法不断提高接收数据内无误码码组的比例进行迭代处理。仿真结果表明，所提算法在不同误码率、不同码长、不同码率、不同码字个数下均优于对比算法。对于IEEE 802.11n协议下的(648,324)LDPC码，当接收码字个数充足时，所提算法在误码率为0.003的条件下，其校验矩阵重建率能达到95%以上；当接收码字个数不足（码字个数为450）时，所提算法在误码率为0.001 5的条件下，其校验矩阵重建率能达到90%以上。

关键词: LDPC, 稀疏校验矩阵, 高斯消元, 剔除错误码字, 对数似然比

Abstract:

In order to improve the performance of the sparse check matrix reconstruction algorithm of LDPC codes at high BER, an open set recognition algorithm of the check matrix with strong fault tolerance under the condition of sufficient and insufficient number of received code words was proposed.Firstly, a new code word space was constructed by randomly extracting part bits of the code words for many times.Gaussian elimination method was used to solve the dual vector and restore the check vector in a lower dimension.Secondly, using the check vector, the proportion of error-free code groups in the received data was continuously increased by using the methods of “eliminating error code words” or“flipping the lowest unreliable bits” for iterative processing.Simulation results show that the proposed algorithm is superior to comparison algorithm under different bit error rates, different code lengths, different code rates and different number of code words.For (648,324) LDPC codes in IEEE 802.11n protocol, when the number of received code words is sufficient, the reconstruction rate of check matrix can reach more than 95% under the condition of bit error rate of 0.003.When the number of received code words is insufficient (the number of code words is 450), the reconstruction rate of check matrix can reach more than 90% under the condition of bit error rate of 0.0015.

Key words: LDPC, sparse check matrix, Gaussian elimination, eliminate error code word, log-likelihood ratio

中图分类号:

TN92

王忠勇, 李正豪, 巩克现, 孙鹏, 李清涛. 高误码率下基于随机抽取的LDPC码校验矩阵重建[J]. 通信学报, 2023, 44(3): 128-137.

Zhongyong WANG, Zhenghao LI, Kexian GONG, Peng SUN, Qingtao LI. Reconstruction of LDPC code check matrix based on random extraction at high bit error rate[J]. Journal on Communications, 2023, 44(3): 128-137.

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高误码率下基于随机抽取的LDPC码校验矩阵重建

Reconstruction of LDPC code check matrix based on random extraction at high bit error rate

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