Quality of Transmission Prediction with Machine Learning for Dynamic Operation of Optical WDM Networks

Abstract

We propose a cognitive scalable method based on neural networks 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-Squared-Error.