Channel-Aware Gradient Descent Bit-Flipping Algorithm for LDPC Codes

The gradient descent bit-flipping with momentum (GDBF-w/M) and probabilistic GDBF-w/M (PGDBF-w/M) algorithms significantly improve the decoding performance of the bit-flipping (BF) algorithm. In this letter, we propose a channel-aware GDBF-w/M algorithm which operates deterministically based on the received values from the additive white Gaussian noise (AWGN) channel. Numerical results show that the proposed algorithm does not only mitigate the error-floor phenomenon of the GDBF-w/M algorithm, but it also has better decoding performance than the PGDBF-w/M algorithm without the need for a random number generator. Furthermore, the complexity of the proposed algorithm is slightly higher than that of the GDBF-w/M algorithm.

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Publication Details

Journal
IEEE Communications Letters
Published
2025-02-20
DOI
https://doi.org/10.1109/lcomm.2025.3543897
Primary Topic
Error Correcting Code Techniques
Type
article
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article

Channel-Aware Gradient Descent Bit-Flipping Algorithm for LDPC Codes

Kyeongcheol Yang, Wu Min
IEEE Communications Letters
Error Correcting Code Techniques
article

Channel-Aware Gradient Descent Bit-Flipping Algorithm for LDPC Codes

Kyeongcheol Yang, Wu Min
article en

Abstract

The gradient descent bit-flipping with momentum (GDBF-w/M) and probabilistic GDBF-w/M (PGDBF-w/M) algorithms significantly improve the decoding performance of the bit-flipping (BF) algorithm. In this letter, we propose a channel-aware GDBF-w/M algorithm which operates deterministically based on the received values from the additive white Gaussian noise (AWGN) channel. Numerical results show that the proposed algorithm does not only mitigate the error-floor phenomenon of the GDBF-w/M algorithm, but it also has better decoding performance than the PGDBF-w/M algorithm without the need for a random number generator. Furthermore, the complexity of the proposed algorithm is slightly higher than that of the GDBF-w/M algorithm.

IEEE Communications LettersVol. 29(4)
Pohang University of Science and Technology (KR)
Openalex Percentile: Top 97%
Error Correcting Code Techniques
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