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arXiv · 2503.17079

Interference Identification in Multi-User Optical Spectrum as a Service using Convolutional Neural Networks

Agastya Raj·Zehao Wang·Frank Slyne·Tingjun Chen·Dan Kilper·Marco Ruffini
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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%.

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Agastya Raj, Zehao Wang, Frank Slyne, Tingjun Chen, Dan Kilper, Marco Ruffini. 2025-03-21. Interference Identification in Multi-User Optical Spectrum as a Service using Convolutional Neural Networks. https://arxiv.org/abs/2503.17079

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