Neural Network Training Framework for Nonlinear Signal-to-Noise Ratio Estimation in Heterogeneous Optical Networks

A computationally efficient framework is presented for calculating features used for training an ANN-based estimator of the nonlinear SNR in heterogeneous networks. Its efficacy is demonstrated using data computed for 153,576 distinct system configurations. © 2021 The Author(s)