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A QoT Estimation Method using EGN-assisted Machine Learning for Network Planning Applications (2112.04039v1)
Published 7 Dec 2021 in cs.NI
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.