Modeling Filtering Penalties in ROADM-Based Networks with Machine Learning for QoT Estimation

Monitoring 3dB bandwidth and other spectrum related parameters at ROADMs provides information about quality of their filters. We propose a machine-learning model to estimate end-to-end filtering penalty for more accurate QoT estimation of future connections.