Filtering Impairments-Aware Digital Twin for SNR Prediction over Network Life-Cycle

We propose a new method to improve SNR prediction of existing and new services with the presence of unknown penalties due to filtering effects. We validate the method in a testbed experiment with 5 OMS and up to 200 deployed services and show an average improvement of SNR service prediction of up to 0.9 dB.