Cost-Gain Analysis of Sequence Selection for Nonlinearity Mitigation
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866915004410757120 |
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| author | Civelli, Stella Secondini, Marco |
| author_facet | Civelli, Stella Secondini, Marco |
| contents | We propose a low-complexity sign-dependent metric for sequence selection and study the nonlinear shaping gain achievable for a given computational cost, establishing a benchmark for future research. Small gains are obtained with feasible complexity. Higher gains are achievable in principle, but with high complexity or a more sophisticated metric. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_02004 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Cost-Gain Analysis of Sequence Selection for Nonlinearity Mitigation Civelli, Stella Secondini, Marco Information Theory Signal Processing We propose a low-complexity sign-dependent metric for sequence selection and study the nonlinear shaping gain achievable for a given computational cost, establishing a benchmark for future research. Small gains are obtained with feasible complexity. Higher gains are achievable in principle, but with high complexity or a more sophisticated metric. |
| title | Cost-Gain Analysis of Sequence Selection for Nonlinearity Mitigation |
| topic | Information Theory Signal Processing |
| url | https://arxiv.org/abs/2411.02004 |