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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/2510.14843 |
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| _version_ | 1866908597989933056 |
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| author | Zahr, Ayman Liva, Gianluigi |
| author_facet | Zahr, Ayman Liva, Gianluigi |
| contents | We analyze by density evolution the asymptotic performance of rate-adaptive MacKay-Neal (MN) code ensembles, where the inner code is a protograph spatially coupled (SC) low-density parity-check code. By resorting to a suitably-defined parallel channel model, we compute belief propagation decoding thresholds, showing that SC MN code ensembles can perform within 0.15 dB from the binary-input additive white Gaussian noise capacity over the full [0,1] rate range. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_14843 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Rate-Adaptive Spatially Coupled MacKay-Neal Codes with Thresholds Close to Capacity Zahr, Ayman Liva, Gianluigi Information Theory We analyze by density evolution the asymptotic performance of rate-adaptive MacKay-Neal (MN) code ensembles, where the inner code is a protograph spatially coupled (SC) low-density parity-check code. By resorting to a suitably-defined parallel channel model, we compute belief propagation decoding thresholds, showing that SC MN code ensembles can perform within 0.15 dB from the binary-input additive white Gaussian noise capacity over the full [0,1] rate range. |
| title | Rate-Adaptive Spatially Coupled MacKay-Neal Codes with Thresholds Close to Capacity |
| topic | Information Theory |
| url | https://arxiv.org/abs/2510.14843 |