Xu, T;
Xu, T;
Darwazeh, I;
(2021)
Deep intelligent spectral labelling and receiver signal distribution for optical links.
Optics Express
, 29
(24)
, Article 39611. 10.1364/OE.422849.
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Abstract
A unique automatic receiver signal distribution strategy is proposed for private optical networks based on the concept of non-orthogonality. A non-orthogonal signal waveform can compress the spectral bandwidth, which not only fits a signal in a bandwidth limited scenario, but also enables the compression ratio information for labelling. Depending on a unique value of spectral compression, an end user destination can be correlated. A network edge node will rely on deep learning to intelligently identify each raw signal and forward it to corresponding end users with no sophisticated digital signal pre-processing. In this case, signal identification and distribution are faster while computationally intensive signal compensation and detection will be shifted to each end user since the receiver is highly dynamic and user-defined in private optical networks. An intelligent signal classifier will be trained considering various fiber transmission factors such as transmission distance, training dataset size and launch power. At the end, a universal classifier is obtained, which can be used to identify signals in a system for any fiber transmission distance and launch power.
| Type: | Article |
|---|---|
| Title: | Deep intelligent spectral labelling and receiver signal distribution for optical links |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1364/OE.422849 |
| Publisher version: | https://doi.org/10.1364/OE.422849 |
| Language: | English |
| Additional information: | © 2021. Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/). |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science 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/10138912 |
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