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Estimating Quality of Transmission in a Live Production Network using Machine Learning

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Abstract

We demonstrate QoT estimation in a live network utilizing neural networks trained on synthetic data spanning a large parameter space. The ML-model predicts the measured lightpath performance with <0.5dB SNR error over a wide configuration range.

© 2021 The Author(s)

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