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

Reviewed by Pithpith:QQEJOIFR open to challenge →

classification cs.NI

keywords networkplanningaccuracyapplicationsaverageclosed-formegn-assistedend-to-end

0 comments

read the original abstract

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.

This paper has not been read by Pith yet.

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

discussion (0)