Analytical QoT models require safety margins to account for uncertain knowledge of input parameters. We propose a new design procedure for restoration planning and upgrade and show up to 19% savings in transponders from lower margins estimated via ML.

ML-Assisted Restoration Planning and Upgrade with Low Design Margins

O. Karandin;F. Musumeci;M. Tornatore
2023-01-01

Abstract

Analytical QoT models require safety margins to account for uncertain knowledge of input parameters. We propose a new design procedure for restoration planning and upgrade and show up to 19% savings in transponders from lower margins estimated via ML.
2023
2023 European Conference on Optical Communication, ECOC 2023
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1260666
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