Machine Learning for QoT Estimation of Unseen Optical Network States
Date
2019Place of publication
San DiegoSource
2019 Optical Fiber Communications Conference and Exhibition (OFC)Pages
1-3Google Scholar check
Metadata
Show full item recordAbstract
We apply deep graph convolutional neural networks for Quality-of-Transmission estimation of unseen network states capturing, apart from other important impairments, the inter-core crosstalk that is prominent in optical networks operating with multicore fibers.