Lennard, S;
Barbosa, FA;
Ferreira, F;
(2024)
Fully Generalized Machine Learning-Based Equalization in Coherent Optical Transmission.
In:
Proceedings of the Advanced Photonics Congress 2024.
(pp. pp. 1-2).
Optica Publishing Group: Québec City, Canada.
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Abstract
We introduce a novel training paradigm for machine learning-based equalization without any online training for dual-polarization IQ-modulated signals. Lab transmission of 30Gbaud DP-16-QAM has shown this equalizer matching conventional DSP over a range of conditions.
| Type: | Proceedings paper |
|---|---|
| Title: | Fully Generalized Machine Learning-Based Equalization in Coherent Optical Transmission |
| Event: | Advanced Photonics Congress 2024 |
| ISBN-13: | 978-1-957171-40-1 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1364/SPPCOM.2024.SpM3G.2 |
| Publisher version: | https://doi.org/10.1364/SPPCOM.2024.SpM3G.2 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10204632 |
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