Neural Network Equalizers and Successive Interference Cancellation for Bandlimited Channels with a Nonlinearity
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arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
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| _version_ | 1866910580910063616 |
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| author | Plabst, Daniel Prinz, Tobias Diedolo, Francesca Wiegart, Thomas Böcherer, Georg Hanik, Norbert Kramer, Gerhard |
| author_facet | Plabst, Daniel Prinz, Tobias Diedolo, Francesca Wiegart, Thomas Böcherer, Georg Hanik, Norbert Kramer, Gerhard |
| contents | Neural networks (NNs) inspired by the forward-backward algorithm (FBA) are used as equalizers for bandlimited channels with a memoryless nonlinearity. The NN-equalizers are combined with successive interference cancellation (SIC) to approach the information rates of joint detection and decoding (JDD) with considerably less complexity than JDD and other existing equalizers. Simulations for short-haul optical fiber links with square-law detection illustrate the gains. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_15767 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Neural Network Equalizers and Successive Interference Cancellation for Bandlimited Channels with a Nonlinearity Plabst, Daniel Prinz, Tobias Diedolo, Francesca Wiegart, Thomas Böcherer, Georg Hanik, Norbert Kramer, Gerhard Information Theory Signal Processing Neural networks (NNs) inspired by the forward-backward algorithm (FBA) are used as equalizers for bandlimited channels with a memoryless nonlinearity. The NN-equalizers are combined with successive interference cancellation (SIC) to approach the information rates of joint detection and decoding (JDD) with considerably less complexity than JDD and other existing equalizers. Simulations for short-haul optical fiber links with square-law detection illustrate the gains. |
| title | Neural Network Equalizers and Successive Interference Cancellation for Bandlimited Channels with a Nonlinearity |
| topic | Information Theory Signal Processing |
| url | https://arxiv.org/abs/2408.15767 |