A QoT Estimation Method using EGN-assisted Machine Learning for Network Planning Applications

Carmen Mas-Machuca; Helmut Griesser; Jasper M\"uller; J\"org-Peter Elbers; Sai Kireet Patri; Tobias Fehenberger

arxiv: 2112.04039 · v1 · pith:QQEJOIFR · submitted 2021-12-07 · cs.NI

A QoT Estimation Method using EGN-assisted Machine Learning for Network Planning Applications

Jasper M\"uller , Sai Kireet Patri , Tobias Fehenberger , Carmen Mas-Machuca , Helmut Griesser , J\"org-Peter Elbers This is my paper

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classification cs.NI

keywords networkplanningaccuracyapplicationsaverageclosed-formegn-assistedend-to-end

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An ML model based on precomputed per-channel SCI is proposed. Due to its superior accuracy over closed-form GN, an average SNR gain of 1.1 dB in an end-to-end link optimization and a 40% reduction in required lightpaths to meet traffic requests in a network planning scenario are shown.

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A QoT Estimation Method using EGN-assisted Machine Learning for Network Planning Applications

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