2000 character limit reached
A QoT Estimation Method using EGN-assisted Machine Learning for Network Planning Applications
Published 7 Dec 2021 in cs.NI | (2112.04039v1)
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.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.