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 0.9dB.
Filtering Impairments-Aware Digital Twin for SNR Prediction over Network Life-Cycle
X. Yang;
2025-01-01
Abstract
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 0.9dB.File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
