A QoT Estimation Method using EGN-assisted Machine Learning for Network Planning Applications
Jasper Müller, Sai Kireet Patri, Tobias Fehenberger, Carmen Mas Machuca, Helmut Grießer, Jörg-Peter Elbers
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.
Topics & Concepts
Computer scienceReduction (mathematics)Channel (broadcasting)Real-time computingComputer networkGeometryMathematicsOptical Network TechnologiesAdvanced Photonic Communication SystemsAdvanced Optical Network Technologies