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)

Forskningsprofessor vid Chalmers, Elektroteknik, Kommunikations- och antennsystem, Optiska nätverk

Marija Furdek Prekratic

Forskarassistent vid Chalmers, Elektroteknik, Kommunikations- och antennsystem, Optiska nätverk

Finansiering

École de Technologie Supérieure (ÉTS)

Finansierar Chalmers deltagande under 2021–2024

National Research Council Canada

Finansierar Chalmers deltagande under 2021–2024

Mer information

Senast uppdaterat

2021-10-01