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

A Grey-box Model for Estimating Nonlinear SNR in Optical Networks Based on Physics-guided Neural Networks

Not Accessible

Your library or personal account may give you access

Abstract

Based on physics-guided neural network, we design the features and loss function for estimating nonlinear SNR. With 1603 examples from simulations, a shallow neural network can have a higher accuracy and a better physical consistency.

© 2021 The Author(s)

PDF Article
More Like This
Neural-network-based MDG and Optical SNR Estimation in SDM Transmission

Ruby S. B. Ospina, Menno van den Hout, Sjoerd van der Heide, Chigo Okonkwo, and Darli A. A. Mello
Th1A.20 Optical Fiber Communication Conference (OFC) 2021

Analysis of Neural Network Compensation for Fiber Nonlinearity in Coherent Optical Communication System Based on Perturbation Model

Tao Xu, Taowei Jin, Wenshan Jiang, Jing Zhang, Xingwen Yi, and Kun Qiu
T4A.37 Asia Communications and Photonics Conference (ACP) 2021

Neural Network Training Framework for Nonlinear Signal-to-Noise Ratio Estimation in Heterogeneous Optical Networks

Aazar S. Kashi, John C. Cartledge, and Wai-Yip Chan
M5F.3 Optical Fiber Communication Conference (OFC) 2021

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.