基于WBP-CNN算法的LDPC译码

doi:10.12305/j.issn.1001-506X.2022.03.36

系统工程与电子技术 ›› 2022, Vol. 44 ›› Issue (3): 1030-1035.doi: 10.12305/j.issn.1001-506X.2022.03.36

基于WBP-CNN算法的LDPC译码

刘恒燕^1,*, 张立民¹, 闫文君¹, 钟兆根¹, 凌青¹, 梁晓军²

1. 海军航空大学航空作战勤务学院, 山东烟台 264001
2. 中国人民解放军第91951部队, 山东威海 264400

收稿日期:2021-01-06 出版日期:2022-03-01 发布日期:2022-03-10
通讯作者: 刘恒燕
作者简介:刘恒燕(1994—), 女, 博士研究生, 主要研究方向为信息系统仿真与智能处理|张立民(1966—), 男, 教授, 博士研究生导师, 博士, 主要研究方向为信息系统仿真与智能处理|闫文君(1986—), 男, 副教授, 博士, 主要研究方向为空时分组码识别、MIMO技术|钟兆根(1984—), 男, 副教授, 博士, 主要研究方向为通信信号盲分离与统计信号处理|凌青(1987—), 女, 副教授, 博士, 主要研究方向为通信信号智能处理|梁晓军(1993—), 男, 本科, 主要研究方向为信息通信系统
基金资助:
国家自然科学基金(91538201);泰山学者工程专项经费基金(ts201511020);信息系统安全技术重点实验室基金(6142111190404)

LDPC decoding based on WBP-CNN algorithm

Hengyan LIU^1,*, Limin ZHANG¹, Wenjun YAN¹, Zhaogen ZHONG¹, Qing LING¹, Xiaojun LIANG²

1. Academy of Aeronautical Operations Service, Naval Aviation University, Yantai 264001, China
2. Unit 91951 of the PLA, Weihai 264400, China

Received:2021-01-06 Online:2022-03-01 Published:2022-03-10
Contact: Hengyan LIU

摘要/Abstract

摘要：

针对低密度奇偶校验(low density parity check, LDPC)码在相关噪声条件下译码误比特率上升的问题, 结合传统译码算法与卷积神经网络(convolutional neural network, CNN)设计了新的译码器。该译码器在置信传播(belief propagation, BP)算法中引入加权比特翻转(weighted bit-flipping, WBF)算法, 生成加权BP(weighted BP, WBP)结构以解决码字临界处误比特率较高的问题。然后通过CNN降低噪声, 在WBP和CNN之间迭代处理接收信号, 使信号估计值不断逼近真实值以降低相关噪声的影响。通过仿真发现, 与BP算法相比, 所提算法能够有效降低相关噪声条件下LDPC译码的误比特率。

关键词: 加权比特翻转, 置信传播, 低密度奇偶校验码译码, 卷积神经网络

Abstract:

Aiming at the problem that the bit error rate of low density parity check (LDPC) codes increases under the condition of correlated noise, a new decoder is designed combined with traditional decoding algorithm and convolutional neural network (CNN). The decoder introduces the weighted bit-flipping (WBF) algorithm into the belief propagation (BP) algorithm to generate a weighted BP (WBP) structure to solve the problem of high bit error rate at the critical point of codeword. Then, the noise is reduced by CNN, and the received signal is processed iteratively between WBP and CNN to make the estimated value of the signal approach the real value continuously, so as to reduce the influence of relevant noise. Simulation results show that compared with BP algorithm, the proposed algorithm can effectively reduce the bit error rate of LDPC decoding under correlated noise.

Key words: weighted bit-flipping (WBF), belief propagation (BP), low density parity check (LDPC) decode, convolutional neural network (CNN)

中图分类号:

TN914

刘恒燕, 张立民, 闫文君, 钟兆根, 凌青, 梁晓军. 基于WBP-CNN算法的LDPC译码[J]. 系统工程与电子技术, 2022, 44(3): 1030-1035.

Hengyan LIU, Limin ZHANG, Wenjun YAN, Zhaogen ZHONG, Qing LING, Xiaojun LIANG. LDPC decoding based on WBP-CNN algorithm[J]. Systems Engineering and Electronics, 2022, 44(3): 1030-1035.

图/表 5

参考文献 30

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基于WBP-CNN算法的LDPC译码

LDPC decoding based on WBP-CNN algorithm

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