QoT Estimation with Margin-Driven Transfer Learning in Time-Varying Optical Networks
Paper i proceeding, 2025
Estimating transmission quality in an optical network is critical for resource efficiency but challenging due to the infrastructure time-varying state. We propose a transfer learning solution to adapt a data-driven model to network changes.
Time-Varying Networks
Artificial Neural Networks
Transfer Learning
QoT Estimation
Författare
Piotr Lechowicz
Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk
Carlos Natalino Da Silva
Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk
Paolo Monti
Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk
2025 Optical Fiber Communications Conference and Exhibition (OFC 2025)
M1J.5
Optical Fiber Communications Conference and Exhibition (OFC 2025)
San Francisco, California, USA,
San Francisco, California, USA,
Ämneskategorier (SSIF 2025)
Telekommunikation