| Issue |
EPJ Web Conf.
Volume 287, 2023
EOS Annual Meeting (EOSAM 2023)
|
|
|---|---|---|
| Article Number | 13022 | |
| Number of page(s) | 2 | |
| Section | Focused Sessions (FS) 4- Machine Learning and Photonic Artificial Intelligence / Optical Neural Networks and Neuromorphic Computing | |
| DOI | https://doi.org/10.1051/epjconf/202328713022 | |
| Published online | 18 October 2023 | |
https://doi.org/10.1051/epjconf/202328713022
Machine learning enabled digital compensation of phase-to-amplitude distor-tion in fibre-optical parametric amplifier based transmission links
Aston Institute of Photonic Technologies, Aston University, Birmingham B4 7ET, United Kingdom
* e-mail: l.nguyen7@aston.ac.uk
Published online: 18 October 2023
We numerically demonstrate an advanced digital signal processing method for compensating the phase-to-amplitude distortion conversion caused by the interaction of the phase noise induced by pump dither-ing with the dispersive fibre channel in fibre-optical parametric amplifier based transmission systems.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.