Adaptive Gradient Descent Bit-Flipping Diversity Decoding
Adaptive Gradient Descent Bit-Flipping Diversity Decoding
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DOI：
10.1109/lcomm.2022.3195026
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发表时间：
2022-10
期刊：
影响因子：
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通讯作者：
Srdan Brkic;P. Ivaniš;B. Vasic
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文献类型：
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作者：
Srdan Brkic;P. Ivaniš;B. Vasic
在这封信中，我们提出了一个用于设计解码器的新型框架，用于低密度奇偶校验检查（LDPC）代码，该框架超过了在二进制对称通道上解码的信念传播（BP）的框架错误率性能。它的关键组成部分是基于遗传优化算法的适应方法，该方法与动量（GDBF-W/M）合并到最近提出的梯度下降位分解中。我们表明，由此产生的解码器的表现优于所有最先进的概率位点式解码器，此外，它可以训练以超出BP解码的方式执行，这可以通过数值示例来验证，这些示例包括IEEE 802.3AN和5GNR中使用的代码标准。提出的框架为解码器优化提供了一种系统的方法，而无需了解陷阱集。此外，它适用于常规和不规则的LDPC代码。
In this letter we propose a novel framework for designing decoders, for Low-Density Parity Check (LDPC) codes, that surpasses the frame error rate performance of Belief-Propagation (BP) decoding on binary symmetric channels. Its key component is the adaptation method, based on the genetic optimization algorithm, that is incorporated into the recently proposed Gradient Descent Bit-Flipping Decoding with Momentum (GDBF-w/M). We show that the resulting decoder outperforms all state-of-the-art probabilistic bit-flipping decoders and, additionally, it can be trained to perform beyond BP decoding, which is verified by numerical examples that include codes used in IEEE 802.3an and 5GNR standards. The proposed framework provides a systematic method for decoder optimization without requiring knowledge of trapping sets. Moreover, it is applicable to both regular and irregular LDPC codes.