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QoT estimation for Unestablished Lightpaths Using Artificial Neural Networks

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Abstract

Estimating the quality of transmission (QoT) for lightpaths is crucial for reducing provisioned margins. We investigate an artificial neural network framework to estimate the QoT of unestablished lightpaths considering interference effects and optical monitoring uncertainties.

© 2018 The Author(s)

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