电子学报 ›› 2020, Vol. 48 ›› Issue (11): 2114-2121.DOI: 10.3969/j.issn.0372-2112.2020.11.004

• 学术论文 • 上一篇    下一篇

CCSDS标准下LDPC码的编译码算法研究

李锦明, 王国栋, 刘梦欣, 张志豪, 郑志旺   

  1. 中北大学仪器与电子学院, 山西太原 030000
  • 收稿日期:2020-01-20 修回日期:2020-07-29 出版日期:2020-11-25
    • 通讯作者:
    • 李锦明
    • 作者简介:
    • 王国栋 男,1995年出生,山西临汾人.现为中北大学研究生,主要研究方向为通信信号处理.E-mail:wangguodongv587@163.com

Research on Encoding and Decoding Algorithm of LDPC Codes Based CCSDS Standard

LI Jin-ming, WANG Guo-dong, LIU Meng-xin, ZHANG Zhi-hao, ZHENG Zhi-wang   

  1. School of Instruments and Electronics, North University of China, Taiyuan, Shanxi 030000, China
  • Received:2020-01-20 Revised:2020-07-29 Online:2020-11-25 Published:2020-11-25

摘要: 低密度奇偶校验(Low Density Parity Check,LDPC)码的译码算法在FPGA实现时常采用整数量化操作,产生误差引起译码性能降低.引入归一化最小和(Normalized Minimum Sum,NMS)译码算法,在校验点信息数据量化的基础上乘以一个取值区间为(0,1)的改进因子减小误差.通过研究改进因子的合理取值,提出了一种随迭代次数取不同改进因子改善量化结果的新量化方法.研究对象为空间数据咨询委员会(The Consultative Committee for Space Data Systems,CCSDS)标准中近地空间应用的(8176,7154)LDPC码,在MATLAB上设计编译码算法程序并完成仿真.仿真结果表明改进量化方法完成译码所需的迭代次数更少,提高了译码性能.通过分析不同信噪比下迭代次数的变化,发现在较高噪声干扰下优势更明显.

关键词: 编译码算法, 低密度奇偶校验码, 量化, MATLAB仿真

Abstract: The decoding algorithm of LDPC codes is often implemented by integer quantization in FPGA,which leads to the degradation of decoding performance.The NMS decoding algorithm is introduced to reduce the error by multiplying an improved factor with a value range of (0,1) on the basis of quantization of check point information data.By studying the reasonable value of the improvement factor,a new quantization method is proposed to improve the quantization results by taking different improvement factors with the iteration times.The research object is the (8176,7154) LDPC code of near earth space application in the CCSDS standard.The encoding and decoding algorithm program is designed and simulated on MATLAB.Simulation results show that the improved quantization method needs less iterations to complete decoding and improves the decoding performance.By analyzing the change of iteration times under different signal-to-noise ratio,the advantage is more obvious under higher noise interference.

Key words: encoding and decoding algorithm, low density parity check (LDPC) code, quantization, MATLAB simulation

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