Smarta optiska nätverk som möjliggörs genom prestandaövervakning och maskininlärning
Forskningsprojekt, 2021
– 2024
The two main objectives of the project are:
(1) investigating machine learning (ML) techniques for quality of transmission (QoT) estimation and prediction in the optical layer;
(2) exploring ML methods for anomaly detection and proactive failure management at the network level.
ML-based methods for QoT estimation and prediction at the physical layer will be explored. ML techniques such as long-term short-memory (LSTM) and neural networks will be investigated for QoT prediction as ways to discover patterns in time-series and achieve dynamic and autonomous system margin control.
Deltagare
Lena Wosinska (kontakt)
Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk
Marija Furdek Prekratic
Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk
Finansiering
National Research Council Canada
Finansierar Chalmers deltagande under 2021–2024
École de Technologie Supérieure (ÉTS)
Finansierar Chalmers deltagande under 2021–2024