Nonlinearity Cancellation Based on Optimized First Order Perturbative Kernels
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866913693216800768 |
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| author | Alvarado, Alex Barreiro, Astrid Liga, Gabriele |
| author_facet | Alvarado, Alex Barreiro, Astrid Liga, Gabriele |
| contents | The potential offered by interference cancellation based on optimized regular perturbation kernels of the Manakov equation is studied. Theoretical gains of up to 2.5 dB in effective SNR are demonstrated. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_11713 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Nonlinearity Cancellation Based on Optimized First Order Perturbative Kernels Alvarado, Alex Barreiro, Astrid Liga, Gabriele Information Theory The potential offered by interference cancellation based on optimized regular perturbation kernels of the Manakov equation is studied. Theoretical gains of up to 2.5 dB in effective SNR are demonstrated. |
| title | Nonlinearity Cancellation Based on Optimized First Order Perturbative Kernels |
| topic | Information Theory |
| url | https://arxiv.org/abs/2502.11713 |