A machine learning approach for dynamic optical channel add/drop strategies that minimize EDFA power excursions
Résumé
We demonstrate a machine learning approach to characterize channel dependence of power excursions in multi-span EDFA networks. This technique can determine accurate recommendations for channel add/drop with minimal excursions and is applicable to different network designs