Interference Identification in Multi-User Optical Spectrum as a Service using Convolutional Neural Networks
Konferenz: ECOC 2024 - 50th European Conference on Optical Communication
22.09.2024-26.09.2024 in Frankfurt, Germany
Tagungsband: ITG-Fb. 317: ECOC 2024
Seiten: 4Sprache: EnglischTyp: PDF
Autoren:
Raj, Agastya; Wang, Zehao; Slyne, Frank; Chen, Tingjun; Kilper, Dan; Ruffini, Marco
Inhalt:
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%.