High Speed Decoding for High-Rate and Short-Length Reed–Muller Code Using Auto-Decoder

نویسندگان

چکیده

In this paper, we show that applying a machine learning technique called auto-decoder (AD) to high-rate and short length Reed–Muller (RM) decoding enables it achieve maximum likelihood (MLD) performance faster speed than when fast Hadamard transform (FHT) is applied in additive white Gaussian noise (AWGN) channels. The approximately 1.8 times 125 the FHT for R(1,4) R(2,4), respectively. number of nodes hidden layer AD larger input layer, unlike conventional auto-encoder (AE). Two ADs are combined parallel merged together, then cascaded one fully connected improve bit error rate (BER) code.

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ژورنال

عنوان ژورنال: Applied sciences

سال: 2022

ISSN: ['2076-3417']

DOI: https://doi.org/10.3390/app12189225