Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
Conferences > ECEOC > 2022 > Mo3A > Mo3A.2
  • European Conference on Optical Communication (ECOC) 2022
  • Technical Digest Series (Optica Publishing Group, 2022),
  • paper Mo3A.2

The Glass of Machine Learning for Quality of Transmission Estimation Is Half Full

Matteo Lonardi, Jelena Pesic, Thierry Zami, Emmanuel Seve, and Nicola Rossi

Not Accessible

Your library or personal account may give you access

Abstract

We discuss an elastic optical network-based approach for evaluating QoT model substitution. Assessing QoT substitution is based on the fundamental idea that different QoT estimators should be examined by analysing their impact integrated with the routing and spectrum allocation algorithm. Machine learning is no exception.

© 2022 The Author(s)

PDF Article
More Like This
The Perks of Using Machine Learning for QoT Estimation with Uncertain Network Parameters

Matteo Lonardi, Jelena Pesic, Thierry Zami, and Nicola Rossi
NeM3B.2 Photonic Networks and Devices (Networks) 2020

Estimating Quality of Transmission in a Live Production Network using Machine Learning

Jasper Müller, Tobias Fehenberger, Sai Kireet Patri, Kaida Kaeval, Helmut Griesser, Marko Tikas, and Jörg-Peter Elbers
Tu1G.2 Optical Fiber Communication Conference (OFC) 2021

Missing Pieces Currently Preventing Effective Application of Machine Learning to QoT Estimation in the Field

Jelena Pesic
M3E.5 Optical Fiber Communication Conference (OFC) 2021

View More...
Select as filters
Select Topics Cancel
Top
       
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.
Privacy | Terms of Use