We present a novel approach for Quality of Transmission estimation using hybrid modelling and transfer-learning. Our method reduces the training data requirement by 80% while obtaining an MSE of 0.27dB. The approach facilitates a streamlined ML life-cycle for data collection, training and deployment.

© 2020 The Author(s)

PDF Article
More Like This
Evol-TL: Evolutionary Transfer Learning for QoT Estimation in Multi-Domain Networks

Che-Yu Liu, Xiaoliang Chen, Roberto Proietti, and S. J. Ben Yoo
Th3D.1 Optical Fiber Communication Conference (OFC) 2020

Transfer learning aided concurrent multi-alarm prediction in optical transport networks

Bing Zhang, Yongli Zhao, Yajie Li, and Jie Zhang
M4A.197 Asia Communications and Photonics Conference (ACPC) 2020

Transfer Learning Using ANN for G-OSNR Estimation in WDM Network Topologies

J. Pesic, M. Lonardi, T. Zami, N. Rossi, and E. Seve
NeM3B.3 Photonic Networks and Devices (Networks) 2020


You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
Login to access Optica Member Subscription