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.

Low-Margin Optical-Network Design with Multiple Physical-Layer Parameter Uncertainties

Karandin O.;Musumeci F.;Tornatore M.
2022-01-01

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.
2022
2022 European Conference on Optical Communication, ECOC 2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1231811
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