Quality of transmission prediction with machine learning for dynamic operation of optical WDM networks
Résumé
We propose a cognitive scalable method based on neural network to address dynamic and agile provisioning of optical physical layer without prior knowledge of network specifications. Experimental demonstrations on a mesh network achieve 90th percentile OSNR prediction of 0.25dB Root-Mean-Suared-Error