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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.15637 |
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| _version_ | 1866911163404517376 |
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| author | Lau, Chin Wa Shi, Xiang Zheng, Ziyan Cao, Haiwen Guo, Nian |
| author_facet | Lau, Chin Wa Shi, Xiang Zheng, Ziyan Cao, Haiwen Guo, Nian |
| contents | Transformer-based neural decoders have emerged as a promising approach to error correction coding, combining data-driven adaptability with efficient modeling of long-range dependencies. This paper presents a novel decoder architecture that integrates classical belief propagation principles with transformer designs. We introduce a differentiable syndrome loss function leveraging global codebook structure and a differential-attention mechanism optimizing bit and syndrome embedding interactions. Experimental results demonstrate consistent performance improvements over existing transformer-based decoders, with our approach surpassing traditional belief propagation decoders for short-to-medium length LDPC codes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_15637 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Interplay Between Belief Propagation and Transformer: Differential-Attention Message Passing Transformer Lau, Chin Wa Shi, Xiang Zheng, Ziyan Cao, Haiwen Guo, Nian Information Theory Signal Processing Transformer-based neural decoders have emerged as a promising approach to error correction coding, combining data-driven adaptability with efficient modeling of long-range dependencies. This paper presents a novel decoder architecture that integrates classical belief propagation principles with transformer designs. We introduce a differentiable syndrome loss function leveraging global codebook structure and a differential-attention mechanism optimizing bit and syndrome embedding interactions. Experimental results demonstrate consistent performance improvements over existing transformer-based decoders, with our approach surpassing traditional belief propagation decoders for short-to-medium length LDPC codes. |
| title | Interplay Between Belief Propagation and Transformer: Differential-Attention Message Passing Transformer |
| topic | Information Theory Signal Processing |
| url | https://arxiv.org/abs/2509.15637 |