卷积码的和积译码

T. Shohon, Y. Ogawa, H. Ogiwara
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引用次数: 7

摘要

本文提出了两种改进卷积码和积软入/软出译码性能的方法。第一种方法是对奇偶校验方程进行变换,去掉卷积码的Tanner图中长度为4的圈,并对变换后的奇偶校验方程进行和积算法(SPA)。该方法提高了(7,5)8卷积码(CC1)的性能。然而,对于(45,73)8卷积码(CC2),该方法不起作用。第二种提出的方法是使用更高阶的奇偶校验方程,与常规的SPA解码奇偶校验方程进行比较。该方法提高了两种卷积码(CC1, CC2)的性能。该算法的性能接近BCJR算法,且复杂度低于BCJR算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sum-product decoding of convolutional codes
This article proposes two methods to improve the sum-product soft-in/soft-out decoding performance of convolutional codes. The first method is to transform a parity check equation in such a way as to remove cycles of length four in a Tanner graph of a convolutional code, and performs sum-product algorithm (SPA) with the transformed parity check equation. This method improves the performance of (7,5)8 convolutional code (CC1). However, for (45,73)8 convolutional code (CC2), the method does not effect. The second proposed method is to use a higher order parity check equation in comparison with a normal parity check equation for SPA decoding. This method improves the performance for both convolutional codes (CC1, CC2). The performance is close to that by BCJR algorithm and it is less complex than BCJR algorithm.
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