Interference Identification in Multi-User Optical Spectrum as a Service using Convolutional Neural Networks
Networking and Internet Architecture
2025-03-24 v1
Abstract
We introduce a ML-based architecture for network operators to detect impairments from specific OSaaS users while blind to the users' internal spectrum details. Experimental studies with three OSaaS users demonstrate the model's capability to accurately classify the source of impairments, achieving classification accuracy of 94.2%.
Keywords
Cite
@article{arxiv.2503.17079,
title = {Interference Identification in Multi-User Optical Spectrum as a Service using Convolutional Neural Networks},
author = {Agastya Raj and Zehao Wang and Frank Slyne and Tingjun Chen and Dan Kilper and Marco Ruffini},
journal= {arXiv preprint arXiv:2503.17079},
year = {2025}
}
Comments
This paper is a preprint of a paper accepted to ECOC 2024 and is subject to Institution of Engineering and Technology Copyright. A copy of record will be available at IET Digital Library