CCSDS标准下LDPC码的编译码算法研究

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.

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

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.