Parameter-Coupled Offset Min-Sum Decoding with Edge-Type Differentiation for MET-LDPC Codes

To improve the decoding performance of multi-edge type low-density parity-check (MET-LDPC) codes, this paper proposes an edge-type differentiated parameter coupling offset min-sum (EDPC-OMS) decoding algorithm. The contributions are threefold. First, we replace the traditional uniform compensation with edge-type differentiated compensation, resolving the mismatch between the decoding model and code structure. Second, we introduce a parameter coupling mechanism that enables joint optimization of multiple edge types while maintaining differentiated configurations. Third, a practically feasible design combining precomputation and look-up tables enables dynamic parameter adjustment with moderate additional overhead, achieving a favorable performance–complexity trade-off. Simulation results over additive white Gaussian noise (AWGN) channels and Rayleigh fading channels demonstrate that the proposed algorithm adaptively selects offset factors according to channel conditions and edge types without introducing significant computational complexity, effectively lowering the bit error rate and enhancing decoding capability.

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Publication Details

Journal
Mathematics
Published
2026-04-17
DOI
https://doi.org/10.3390/math14081352
Primary Topic
Error Correcting Code Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Parameter-Coupled Offset Min-Sum Decoding with Edge-Type Differentiation for MET-LDPC Codes

Weiwei Lin, Guodong Su, Ying You
Mathematics
Error Correcting Code Techniques
article

Parameter-Coupled Offset Min-Sum Decoding with Edge-Type Differentiation for MET-LDPC Codes

Weiwei Lin, Guodong Su, Ying You
article en

Abstract

To improve the decoding performance of multi-edge type low-density parity-check (MET-LDPC) codes, this paper proposes an edge-type differentiated parameter coupling offset min-sum (EDPC-OMS) decoding algorithm. The contributions are threefold. First, we replace the traditional uniform compensation with edge-type differentiated compensation, resolving the mismatch between the decoding model and code structure. Second, we introduce a parameter coupling mechanism that enables joint optimization of multiple edge types while maintaining differentiated configurations. Third, a practically feasible design combining precomputation and look-up tables enables dynamic parameter adjustment with moderate additional overhead, achieving a favorable performance–complexity trade-off. Simulation results over additive white Gaussian noise (AWGN) channels and Rayleigh fading channels demonstrate that the proposed algorithm adaptively selects offset factors according to channel conditions and edge types without introducing significant computational complexity, effectively lowering the bit error rate and enhancing decoding capability.

MathematicsVol. 14(8)
Fujian Normal University (CN), Xiamen University of Technology (CN)
National Natural Science Foundation of China, Natural Science Foundation of Fujian Province
Openalex Percentile: Top 19%
Error Correcting Code Techniques
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