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Machine Learning for QoT Estimation of Unseen Optical Network States

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Abstract

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.

© 2019 The Author(s)

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