CAJ | 학술논문

低密度奇偶校验码（low-density parity-check codes，LDPC）以其接近香农极限的性能和相对简单的译码结构得到信道编码界的广泛关注。对 LDPC 码的最小和算法进行了深入地研究，通过多种方法量化译码时的初始消息，最终使得每次迭代的校验消息与变量消息都变为整数，实现了基于整数运算的最小和译码算法，并进行了对比分析。仿真表明，量化后的最小和算法中的所有变量都用固定长度的整数表示，因而便于硬件实现，在其译码性能比和积译码（sum-product decoding，SP）性能下降不大的情况下大大提高了译码速度；平均互信息越大的量化方法，其量化分层电平也越佳；最大平均互信息量化下的最小和译码算法性能最好，最大平均互信息量化是一类能最大可能获得信源信息条件下的最佳量化方法，且不增加译码复杂度。
저밀도기우교험마（low-density parity-check codes，LDPC）이기접근향농겁한적성능화상대간단적역마결구득도신도편마계적엄범관주。대 LDPC 마적최소화산법진행료심입지연구，통과다충방법양화역마시적초시소식，최종사득매차질대적교험소식여변량소식도변위정수，실현료기우정수운산적최소화역마산법，병진행료대비분석。방진표명，양화후적최소화산법중적소유변량도용고정장도적정수표시，인이편우경건실현，재기역마성능비화적역마（sum-product decoding，SP）성능하강불대적정황하대대제고료역마속도；평균호신식월대적양화방법，기양화분층전평야월가；최대평균호신식양화하적최소화역마산법성능최호，최대평균호신식양화시일류능최대가능획득신원신식조건하적최가양화방법，차불증가역마복잡도。
Low-density parity-check (LDPC)codes become popular for its near Shannon limit performance and relatively simple decoding structure.The min-sum decoding algorithm of LDPC codes is studied detailedly. And the variable message and check message of each iteration become integers through a variety of methods quantifying the initial message.Then the integer arithmetic based on the min-sum decoding algorithm is real-ized.Finally,these algorithms are compared and analyzed.Simulation results show that all variables of the min-sum decoding algorithm are fixed length integers after quantification.It is easy for hardware implementation. And the decoding time is greatly shortened under the condition that the decoding performance degrades less than the sum-product (SP)decoding.The greater the average mutual information of the quantitative method is,the better the quantized level will be.The min-sum decoding algorithm of the maximum average mutual information quantization has the best performance.The maximum average mutual information quantization is the best quan-titative method to keep the source information as much as possible,and it does not increase the complexity of de-coding.