Branch Identification in Passive Optical Networks using Machine Learning
arXiv:2304.00285v110 citationsh-index: 30
Originality Incremental advance
AI Analysis
This work addresses monitoring challenges in passive optical networks, which is an incremental improvement for network operators.
The paper tackled the problem of monitoring passive optical networks with nearly equidistant branches by proposing a machine learning approach, achieving a diagnostic accuracy of 98.7% and an event localization error of 0.5m.
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