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Machine Learning for QoT Estimation of Unseen Optical Network States
Published 18 Dec 2018 in cs.NI and eess.SP | (1812.07254v1)
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.
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