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.
|Title of host publication||2022 European Conference on Optical Communication, ECOC 2022|
|Number of pages||4|
|Publication status||Published - 20 Dec 2022|
|Event||2022 European Conference on Optical Communication, ECOC 2022 - Basel, Switzerland|
Duration: 18 Sept 2022 → 22 Sept 2022
|Name||2022 European Conference on Optical Communication, ECOC 2022|
|Conference||2022 European Conference on Optical Communication, ECOC 2022|
|Period||18/09/22 → 22/09/22|
Bibliographical noteFunding Information:
Acknowledgements: This work has been supported by the EU H2020 Marie Skodowska-Curie Action project REAL-NET (No. 813144) and EPSRC project TRANSNET.
© 2022 Optica.
- optical fibers
- artificicial neural networks
- optical fiber networks
- fiber nonlinear optics
- complexity theory