most citedFaulty Branch Identification in Passive Optical Networks using Machine Learning

23 citations · 23 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2024

Threat Classification on Deployed Optical Networks Using MIMO Digital Fiber Sensing, Wavelets, and Machine Learning

Khouloud Abdelli, Henrique Pavani, Christian Dorize +4

We demonstrate mechanical threats classification including jackhammers and excavators, leveraging wavelet transform of MIMO-DFS output data across a 57-km operational network link.…

cs.NI2024

Weather-Adaptive Multi-Step Forecasting of State of Polarization Changes in Aerial Fibers Using Wavelet Neural Networks

Khouloud Abdelli, Matteo Lonardi, Jurgen Gripp +2

We introduce a novel weather-adaptive approach for multi-step forecasting of multi-scale SOP changes in aerial fiber links. By harnessing the discrete wavelet transform and incorpo…

cs.LG2024

Unsupervised Anomaly Detection and Localization with Generative Adversarial Networks

Khouloud Abdelli, Matteo Lonardi, Jurgen Gripp +3

We propose a novel unsupervised anomaly detection approach using generative adversarial networks and SOP-derived spectrograms. Demonstrating remarkable efficacy, our method achieve…

cs.LG202323 cited

Faulty Branch Identification in Passive Optical Networks using Machine Learning

Khouloud Abdelli, Carsten Tropschug, Helmut Griesser +1

Passive optical networks (PONs) have become a promising broadband access network solution. To ensure a reliable transmission, and to meet service level agreements, PON systems have…

cs.LG2023

Branch Identification in Passive Optical Networks using Machine Learning

khouloud Abdelli, Carsten Tropschug, Helmut Griesser +2

A machine learning approach for improving monitoring in passive optical networks with almost equidistant branches is proposed and experimentally validated. It achieves a high diagn…