Low-Density Parity-Check Decoding Algorithm Based on Symmetric Alternating Direction Method of Multipliers

The Alternating Direction Method of Multipliers (ADMM) has proven to be an efficient approach for implementing linear programming (LP) decoding of low-density parity-check (LDPC) codes. By introducing penalty terms into the LP decoding model's objective function, ADMM-based variable node penalized decoding effectively mitigates non-integral solutions, thereby improving frame error rate (FER) performance, especially in the low signal-to-noise ratio (SNR) region. In this paper, we leverage the ADMM framework to derive explicit iterative steps for solving the LP decoding problem for LDPC codes with penalty functions. To further enhance decoding efficiency and accuracy, We propose an LDPC code decoding algorithm based on the symmetric ADMM (S-ADMM). We also establish some contraction properties satisfied by the iterative sequence of the algorithm. Through simulation experiments, we evaluate the proposed S-ADMM decoder using three standard LDPC codes and three representative fifth-generation (5G) codes. The results show that the S-ADMM decoder consistently outperforms conventional ADMM penalized decoders, offering significant improvements in decoding performance.

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Publication Details

Journal
Entropy
Published
2025-04-09
DOI
https://doi.org/10.3390/e27040404
Primary Topic
Error Correcting Code Techniques
Type
article
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article

Low-Density Parity-Check Decoding Algorithm Based on Symmetric Alternating Direction Method of Multipliers

Huaan Li, Hengzhou Xu, Ying Zhang, Baofeng Ji et al.
Entropy
Error Correcting Code Techniques
article

Low-Density Parity-Check Decoding Algorithm Based on Symmetric Alternating Direction Method of Multipliers

Huaan Li, Hengzhou Xu, Ying Zhang, Baofeng Ji, Ji Zhang, Anmin Chen
article en

Abstract

The Alternating Direction Method of Multipliers (ADMM) has proven to be an efficient approach for implementing linear programming (LP) decoding of low-density parity-check (LDPC) codes. By introducing penalty terms into the LP decoding model's objective function, ADMM-based variable node penalized decoding effectively mitigates non-integral solutions, thereby improving frame error rate (FER) performance, especially in the low signal-to-noise ratio (SNR) region. In this paper, we leverage the ADMM framework to derive explicit iterative steps for solving the LP decoding problem for LDPC codes with penalty functions. To further enhance decoding efficiency and accuracy, We propose an LDPC code decoding algorithm based on the symmetric ADMM (S-ADMM). We also establish some contraction properties satisfied by the iterative sequence of the algorithm. Through simulation experiments, we evaluate the proposed S-ADMM decoder using three standard LDPC codes and three representative fifth-generation (5G) codes. The results show that the S-ADMM decoder consistently outperforms conventional ADMM penalized decoders, offering significant improvements in decoding performance.

EntropyVol. 27(4)
Henan University of Science and Technology (CN), Zhoukou Normal University (CN), Henan University of Engineering (CN), Luoyang Institute of Science and Technology (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 93%
Error Correcting Code Techniques
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