Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Dynamic Power Pre-adjustments with Machine Learning that Mitigate EDFA Excursions during Defragmentation

Not Accessible

Your library or personal account may give you access

Abstract

We examine EDFA power excursions during three defragmentation methods of flexgrid super-channels. Using a machine learning approach, we demonstrate automatic and dynamic adjustments of pre-EDFA power levels, and show the mitigation of post-EDFA power discrepancy among channels by over 62%.

© 2017 Optical Society of America

PDF Article
More Like This
Power Excursion Reduction in Flex-Grid Optical Networks with Symbol Rate Adaptation

Djamel Amar, Payman Samadi, Keren Bergman, Catherine Lepers, Mounia Lourdiane, Cedric Ware, and Philippe Gravey
S4C.5 Asia Communications and Photonics Conference (ACP) 2017

Optical Amplifier Control in Optical Networks using Machine Learning

Catherine Lepers, Maria Freire-Hermelo, Antoine Lavignotte, Dipankar Sengupta, and Christine Tremblay
NeM3B.5 Photonic Networks and Devices (Networks) 2020

Predicting Optical Power Excursions in Erbium Doped Fiber Amplifiers using Neural Networks

Maria Freire, Sebastien Mansfeld, Djamel Amar, Franck Gillet, Antoine Lavignotte, and Catherine Lepers
Su3C.7 Asia Communications and Photonics Conference (ACP) 2018

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All Rights Reserved