Abstract
For the first time, recurrent and feedforward neural network-based equalizers for nonlinearity compensation are implemented in an FPGA, with a level of complexity comparable to that of a dispersion equalizer. We demonstrate that the NN-based equalizers can outperform a 1-step-per-span DBP.
Original language | English |
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Title of host publication | 2022 European Conference on Optical Communication, ECOC 2022 |
Publisher | IEEE |
Number of pages | 4 |
ISBN (Electronic) | 9781957171159 |
Publication status | Published - 20 Dec 2022 |
Event | 2022 European Conference on Optical Communication, ECOC 2022 - Basel, Switzerland Duration: 18 Sept 2022 → 22 Sept 2022 |
Publication series
Name | 2022 European Conference on Optical Communication, ECOC 2022 |
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Conference
Conference | 2022 European Conference on Optical Communication, ECOC 2022 |
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Country/Territory | Switzerland |
City | Basel |
Period | 18/09/22 → 22/09/22 |
Bibliographical note
Funding Information:Acknowledgements: This work has been supported by the EU H2020 Marie Skodowska-Curie Action project REAL-NET (No. 813144) and EPSRC project TRANSNET.
Publisher Copyright:
© 2022 Optica.
Keywords
- optical fibers
- equalizers
- Europe
- artificicial neural networks
- optical fiber networks
- fiber nonlinear optics
- complexity theory