极化码解码器的优化研究

发布时间：2018-03-01 09:19

本文关键词： 极化码信道极化连续消除解码校正判定　出处：《西北农林科技大学》2017年硕士论文　论文类型：学位论文

【摘要】：极化码是Arikan在2009年提出的一种新的编码方法,它是目前唯一一个被证明在二进制离散无记忆信道中码长足够长的情况下能够达到香农极限的编码,这种编码方法是基于信道极化现象,利用信道组合和信道拆分构造的一种编码。极化码在码长无限长的条件下才能达到香农极限,但是在实际通信使用中码长无限长基本是不可能的。因此,极化码在码长有限的条件下,寻找有效的解码算法还需要更多的研究。本文通过对极化码连续消除译码算法的研究,提出一种优化方案,该方案将解码中信息位的判定条件改进为依据下个信息位在当前信息位两种情况下的LR值对比结果,并给出改进解码算法的复杂度。具体研究内容和结论如下:(1)分析了极化码的基本原理。详细讨论了极化码的信道组合、信道拆分以及信道极化现象。并讨论了极化码在二进制高斯信道下的极化方式,给出了相应的Z参数计算方法。(2)对极化码的编解码进行了详细研究。极化码的编码过程比较直观,编码中最主要的部分是获取生成矩阵和信道挑选。在解码方面对极化码的SC译码算法进行了详细分析,译码过程是采用递归的方法,信息位的判定是依据当前计算的LR值。在高斯信道中对SC译码算法进行仿真实现,对其解码性能进行分析,并发现SC解码器在码长有限的情况下性能较低的缺陷,提出优化的关键点。(3)基于SC解码算法提出优化方案并给出详细的解码设计。在解码过程中,优化的解码算法对当前信息位的判定需要依据下个信息位在当前信息位为0和1的条件下的LR值的对比,这种方法降低了整个解码过程的错误率。通过码树分析对比改进的算法与SC解码算法的计算流程,给出了优化的解码算法的复杂度。通过仿真实验,对比优化的解码与SC解码的性能,证明了优化的解码算法的误码率低于SC解码,并对误码率曲线进行了分析。
[Abstract]:Polarization code is a new coding method proposed by Arikan in 2009. It is the only code that has been proved to reach Shannon limit in binary discrete memoryless channel when the code length is long enough. This coding method is based on the phenomenon of channel polarization, which is constructed by channel combination and channel splitting. The polarization code can reach Shannon limit under the condition that the code length is infinite. However, it is impossible to use infinite code length in practical communication. Therefore, more research is needed to find effective decoding algorithm under the condition of limited code length. In this paper, we study the continuous elimination decoding algorithm of polarimetric code. An optimization scheme is proposed, in which the decision condition of information bit in decoding is improved as the comparison result of LR value of the next information bit in two cases of current information bit. And the complexity of the improved decoding algorithm is given. The detailed research contents and conclusions are as follows: 1) the basic principle of polarization code is analyzed, and the channel combination of polarization code is discussed in detail. The polarization mode of polarization code in binary Gao Si channel is discussed. The corresponding Z parameter calculation method is given. The encoding and decoding of polarization code is studied in detail. The encoding process of polarization code is more intuitive. The most important part of the coding is to obtain the generation matrix and channel selection. In the aspect of decoding, the SC decoding algorithm of polarization code is analyzed in detail. The decision of the information bit is based on the current calculated LR value. The SC decoding algorithm is simulated in Gao Si channel, and its decoding performance is analyzed. It is found that the SC decoder has a low performance in the case of limited code length. The key point of optimization is put forward. (3) based on SC decoding algorithm, the optimization scheme and detailed decoding design are presented. The decision of the current information bit by the optimized decoding algorithm needs to be compared with the LR value of the next information bit under the condition that the current information bit is 0 and 1. This method reduces the error rate of the whole decoding process. The complexity of the optimized decoding algorithm is given by comparing the improved algorithm with the SC decoding algorithm by code tree analysis. Comparing the performance of optimized decoding and SC decoding, it is proved that the BER of the optimized decoding algorithm is lower than that of SC decoding, and the BER curve is analyzed.
【学位授予单位】：西北农林科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN911.22

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