用卷积神经网络确定LDPC码字大小

B. Comar
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摘要

本文讨论了一种前向纠错(FEC)码分类系统的设计和性能,该系统用于从比特流中确定未知码字的大小。该分类系统是一个深度神经网络,在半速率低密度奇偶校验(LDPC)码上进行训练和测试。测试使用多达250种不同大小的码字流进行。基于CNN的分类器表现非常好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
LDPC Codeword Size Determination Using Convolutional Neural Networks
This paper discusses the design and performance of a forward error correction (FEC) code classification system that is used to determine the size of an unknown codeword from a stream of bits. The classification system is a deep neural network that is trained and tested on half rate low density parity check (LDPC) codes. Tests were performed on streams of codewords using codes of up to 250 different sizes. The CNN based classifier performs very well.
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