LDPC码梯度下降翻转译码的转义方案

Hua Li, Hong Ding, Linhua Zheng
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引用次数: 2

摘要

梯度下降比特翻转(GDBF)译码算法与其他比特翻转(BF)译码算法相比,在性能和复杂度之间取得了很好的平衡。然而,无限循环的译码严重影响了GDBF的译码性能,在达到最大迭代次数时往往会导致译码失败。为了避免解码循环,提高性能,本文提出了一种高效的GDBF转义方案。该方案首先引入综合征权重来检测解码环路。如果检测到解码循环,则转义机制工作,其中只选择最有效地降低综合征权重的位进行翻转。此外,引入排除集进一步防止局部最大值。仿真结果表明,采用该方案,GDBF算法可获得约1db的码增益。与噪声GDBF相比,它的性能损失为0.1dB,且复杂度更低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An escaping scheme for gradient descent bit-flipping decoding of LDPC codes
The gradient descent bit-flipping (GDBF) decoding algorithm offers an attractive tradeoff between performance and complexity compared with the other bit-flipping (BF) decoding algorithms. However, the performance of GDBF decoding is seriously effected by infinite decoding loop, which always results in decoding failure when maximal iteration number is reached. To avoid the decoding loop and improve the performance, an efficient escaping scheme is proposed for the GDBF algorithm in this paper. This scheme firstly introduces syndrome weight to detect the decoding loop. If a decoding loop is detected, the escaping mechanism works, where only the bit which can decrease the syndrome weight most efficiently is selected to be flipped. In addition, the excluding set is introduced to further prevent the local maximum. Simulation results show that the GDBF algorithm can obtain about 1 dB code gain by utilizing this scheme. Compared with noise GDBF, it has 0.1dB performance loss as well as lower complexity.
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