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A machine learning approach for improving monitoring in passive optical networks with almost equidistant branches is proposed and experimentally validated. It achieves a high diagnostic accuracy of 98.7% and an event localization error of 0.5m
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@article{abdelli2023branch,
title = {Branch Identification in Passive Optical Networks using Machine Learning},
author = {khouloud Abdelli and Carsten Tropschug and Helmut Griesser and Sander Jansen and Stephan Pachnicke},
year = {2023},
eprint = {2304.00285},
archivePrefix = {arXiv},
url = {http://arxiv.org/abs/2304.00285v1}
}Shows whether official code is linked for this paper.
[](https://codeofpaper.com/paper/2304.00285)