Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Machine learning Assisted Accurate Estimation of QoT Impairments of Photonics Switching System on 400ZR

Not Accessible

Your library or personal account may give you access

Abstract

We propose a machine learning-based technique that accurately estimates quality-of-transmission (QoT) impairments of an optical switch on 400ZR. The proposed scheme works in an entirely agnostic way reduces inaccuracy in QoT impairments estima­tion by 1.5 dB.

© 2021 The Author(s)

PDF Article
More Like This
Machine Learning Assisted Model of QoT Penalties for Photonics Switching Systems

Ihtesham Khan, Lorenzo Tunesi, Muhammad Umar Masood, Enrico Ghillino, Paolo Bardella, Andrea Carena, and Vittorio Curri
M2A.3 Photonics in Switching and Computing (PS) 2021

Machine Learning Assisted Management of Photonic Switching Systems

Ihtesham Khan, M Umar Masood, Lorenzo Tunesi, Paolo Bardella, Enrico Ghillino, Andrea Carena, and Vittorio Curri
JTu3A.32 CLEO: Applications and Technology (CLEO:A&T) 2021

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All Rights Reserved