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
In corso di stampa
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.File in questo prodotto:
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