Capacity-achieving sparse superposition codes with spatially coupled VAMP decoder
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866917989851332608 |
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| author | Liu, Yuhao Fu, Teng Fan, Jie Niu, Panpan Deng, Chaowen Huang, Zhongyi |
| author_facet | Liu, Yuhao Fu, Teng Fan, Jie Niu, Panpan Deng, Chaowen Huang, Zhongyi |
| contents | Sparse superposition (SS) codes provide an efficient communication scheme over the Gaussian channel, utilizing the vector approximate message passing (VAMP) decoder for rotational invariant design matrices. Previous work has established that the VAMP decoder for SS achieves Shannon capacity when the design matrix satisfies a specific spectral criterion and exponential decay power allocation is used. In this work, we propose a spatially coupled VAMP (SC-VAMP) decoder for SS with spatially coupled design matrices. Based on state evolution (SE) analysis, we demonstrate that the SC-VAMP decoder is capacity-achieving when the design matrices satisfy the spectra criterion. Empirically, we show that the SC-VAMP decoder outperforms the VAMP decoder with exponential decay power allocation, achieving a lower section error rate. All codes are available on https://github.com/yztfu/SC-VAMP-for-Superposition-Code.git. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2504_13601 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Capacity-achieving sparse superposition codes with spatially coupled VAMP decoder Liu, Yuhao Fu, Teng Fan, Jie Niu, Panpan Deng, Chaowen Huang, Zhongyi Information Theory Sparse superposition (SS) codes provide an efficient communication scheme over the Gaussian channel, utilizing the vector approximate message passing (VAMP) decoder for rotational invariant design matrices. Previous work has established that the VAMP decoder for SS achieves Shannon capacity when the design matrix satisfies a specific spectral criterion and exponential decay power allocation is used. In this work, we propose a spatially coupled VAMP (SC-VAMP) decoder for SS with spatially coupled design matrices. Based on state evolution (SE) analysis, we demonstrate that the SC-VAMP decoder is capacity-achieving when the design matrices satisfy the spectra criterion. Empirically, we show that the SC-VAMP decoder outperforms the VAMP decoder with exponential decay power allocation, achieving a lower section error rate. All codes are available on https://github.com/yztfu/SC-VAMP-for-Superposition-Code.git. |
| title | Capacity-achieving sparse superposition codes with spatially coupled VAMP decoder |
| topic | Information Theory |
| url | https://arxiv.org/abs/2504.13601 |