QoT Estimation with Margin-Driven Transfer Learning in Time-Varying Optical Networks
Paper in 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.
QoT Estimation
Artificial Neural Networks
Time-Varying Networks
Transfer Learning
Author
Piotr Lechowicz
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Carlos Natalino Da Silva
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Paolo Monti
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
2025 Optical Fiber Communications Conference and Exhibition (OFC 2025)
M1J.5
978-1-55752-737-0 (ISBN)
2025 Optical Fiber Communications Conference and Exhibition-OFC
San Francisco, California, USA,
San Francisco, California, USA,
Subject Categories (SSIF 2025)
Telecommunications
DOI
10.1364/OFC.2025.M1J.5