SOGRAND Assisted Guesswork Reduction
Fuente:
arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866914204858974208 |
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| author | Rapp, Lukas Médard, Muriel Duffy, Ken R. |
| author_facet | Rapp, Lukas Médard, Muriel Duffy, Ken R. |
| contents | Proposals have been made to reduce the guesswork of Guessing Random Additive Noise Decoding (GRAND) for binary linear codes by leveraging codebook structure at the expense of degraded block error rate (BLER). We establish one can preserve guesswork reduction while eliminating BLER degradation through dynamic list decoding terminated based on Soft Output GRAND's error probability estimate. We illustrate the approach with a method inspired by published literature and compare performance with Guessing Codeword Decoding (GCD). We establish that it is possible to provide the same BLER performance as GCD while reducing guesswork by up to a factor of 32. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_22885 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | SOGRAND Assisted Guesswork Reduction Rapp, Lukas Médard, Muriel Duffy, Ken R. Information Theory Proposals have been made to reduce the guesswork of Guessing Random Additive Noise Decoding (GRAND) for binary linear codes by leveraging codebook structure at the expense of degraded block error rate (BLER). We establish one can preserve guesswork reduction while eliminating BLER degradation through dynamic list decoding terminated based on Soft Output GRAND's error probability estimate. We illustrate the approach with a method inspired by published literature and compare performance with Guessing Codeword Decoding (GCD). We establish that it is possible to provide the same BLER performance as GCD while reducing guesswork by up to a factor of 32. |
| title | SOGRAND Assisted Guesswork Reduction |
| topic | Information Theory |
| url | https://arxiv.org/abs/2503.22885 |