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Iterative soft-decision decoding of Hermitian codes

机译:埃尔米特码的迭代软判决解码

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Algebraic-geometric (AG) codes have long been identified as a possible candidate to replace Reed-Solomon (RS) codes for error-correction. This paper proposes an iterative soft-decision decoding algorithm for one of the most popular AG codes - Hermitian codes. The algorithm is designed by integrating the legacy belief propagation (BP) algorithm and the Koetter-Vardy (KV) soft-decision list decoding algorithm. The BP algorithm performs iterative decoding based on an adapted parity-check matrix whose density has been reduced, namely the adaptive BP (ABP) algorithm. It enhances the reliability of the received information, with which the KV algorithm performs soft-decision list decoding to obtain the intended message. Since the matrix adaptation is bit reliability oriented, re-grouping of the unreliable bits is introduced to assist the ABP algorithm. Geometric analysis of the ABP algorithm is presented, demonstrating the necessity of performing matrix adaptation and integrating the ABP and KV algorithms. The performance evaluation shows the proposed iterative decoding algorithm is an advanced decoding approach that outperforms the existing decoding algorithms for Hermitian codes. It can also outperform ABP-KV decoding of RS codes.
机译:长期以来,代数几何(AG)代码已被认为是代替Reed-Solomon(RS)代码进行纠错的一种可能方法。本文提出了一种最流行的AG码-Hermitian码的迭代软判决解码算法。该算法是通过将传统信念传播(BP)算法和Koetter-Vardy(KV)软决策列表解码算法集成在一起而设计的。 BP算法基于密度已降低的自适应奇偶校验矩阵(即自适应BP(ABP)算法)执行迭代解码。它提高了接收到的信息的可靠性,KV算法使用该算法执行软决策列表解码以获得所需的消息。由于矩阵自适应是面向位可靠性的,因此引入了不可靠位的重新分组以辅助ABP算法。提出了ABP算法的几何分析,证明了执行矩阵自适应以及将ABP和KV算法集成在一起的必要性。性能评估表明,所提出的迭代解码算法是一种先进的解码方法,其性能优于现有的埃尔米特码解码算法。它也可以胜过RS码的ABP-KV解码。

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