在MSA复杂度下的接近lspa性能

J. Andrade, G. F. P. Fernandes, V. Silva, J. Barreto, Nuno Gonçalves, V. Savin
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引用次数: 17

摘要

LDPC译码算法在纠错性能和数值复杂度之间的权衡是一个众所周知的问题。本文描述了长长度DVB-S2码的自校正最小和算法的隐错层性能。我们使用gpu开发了一个大规模并行模拟,允许在瀑布或误差层区域进行全面的误码率表征。研究表明,与最小和算法相比,自校正技术在瀑布和误差层区域的误码率性能分别提高了0.5和0.2 dB。此外,它达到0.2 dB以内的对数和积误码率性能,并且在高信噪比下也优于归一化最小和算法,这是一种低复杂度的解码算法,具有良好的误码率性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Near-LSPA performance at MSA complexity
The tradeoff between error-correcting performance and numerical complexity of LDPC decoding algorithms is a well-known problem. In this paper we depict the unseen error-floor performance of the Self-Corrected Min-Sum algorithm for long length DVB-S2 codes. We developed a massively parallel simulation using GPUs which allowed a comprehensive BER characterization either in the waterfall or in the error-floor region. We show that the self-correction technique increases the BER performance by 0.5 and 0.2 dB, in the waterfall and error-floor region, when compared to the Min-Sum algorithm. Furthermore, it reaches within 0.2 dB to the Logarithmic Sum-Product BER performance and it also outperforms the Normalized Min-Sum at high SNR, a low complexity decoding algorithm which yields good BER performance.
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