Abstract:
Analytical QoT models require safety margins to account for uncertain knowledge of input parameters. We propose and evaluate a design procedure that gradually decreases t...Show MoreMetadata
Abstract:
Analytical QoT models require safety margins to account for uncertain knowledge of input parameters. We propose and evaluate a design procedure that gradually decreases these margins in presence of multiple physical-layer uncertainties, by leveraging monitoring data to build a ML-based QoT regressor.
Published in: 2022 European Conference on Optical Communication (ECOC)
Date of Conference: 18-22 September 2022
Date Added to IEEE Xplore: 20 December 2022
ISBN Information:
Conference Location: Basel, Switzerland