利用最大偏差比的LDPC码识别算法

An Identification Algorithm for LDPC Codes Using Maximum Deviation Ratio

  • 摘要: 随着自适应调制编码技术(简称AMC)的广泛应用,信道编码识别技术已经引起研究人员越来越多的关注。本文提出了一种在AMC技术中基于最大偏差比的LDPC码识别算法。文章首先利用随着自适应调制编码技术(AMC)和低密度奇偶校验码(LDPC)的广泛应用,AMC框架下的LDPC码识别技术已引起研究人员越来越多的关注。已有的识别算法存在识别性能不足的问题,为此,本文提出了一种AMC框架下基于最大偏差比的LDPC码识别算法。文章首先利用软判决接收序列定义了编码校验关系的对数似然比(PLLR),并对其模值的概率分布函数进行了分析;然后,利用不同校验矩阵下,校验关系对数似然比统计特性的差异,提出了一种可兼顾PLLR均值和方差特征的最大偏差比判决器。仿真结果表明,在AMC框架下,本文识别算法能够有效地完成对LDPC码的识别,且在低信噪比条件下仍能获得较好的识别结果,特别地,针对高码率LDPC码识别问题时,新算法性能优于已有算法。

     

    Abstract: With the extensive application of adaptive modulation and coding techniques (AMC) and low density parity codes (LDPC), identification technology for LDPC in AMC has drawn more and more researchers’ attention. For that problem, the existing methods have been suffering weak identification performance, so this paper presents a new recognition algorithm for LDPC in AMC based on maximum deviation ratio. First, the paper defines the log-likelihood ratio (PLLR) of the parity relationship with the soft-decision sequence, and makes some necessary analysis on its module value’s probability distribution. Then, using the statistical differences of the parity log-likelihood ratio on the various parity check matrix, a maximum deviation ratio based decision device is proposed, which takes into account both mean and variation properties of PLLR. Simulation results show that the new recognition algorithm can effectively identify the LDPC codes in AMC, even in the low signal-to-noise ratio channel environments. Especially for the high code rate LDPC codes, the new algorithm is better than existing ones.

     

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