Power Profile Estimation of Optical Transmission Links Based on Machine Learning
- 12 August 2021
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Photonics Technology Letters
- Vol. 33 (19), 1089-1092
- https://doi.org/10.1109/lpt.2021.3104508
Abstract
We propose a method for estimation of power profile in optical transmissions by employing machine learning optimization to a digital back-propagation model. The method allows to estimate the absolute power values along the link and it requires solely the coherently acquired data at the receiver-side. The estimated values are validated using experimental results from an unrepeatered transmission, employing remote and Raman amplification.Keywords
Funding Information
- Brazilian Fundo para o Desenvolvimento Tecnológico das Telecomunicações
- Financiadora de Estudos e Projetos (Finep) and Conselho Nacional de Desenvolvimento Científico e Tecnológico
This publication has 6 references indexed in Scilit:
- Digital Backpropagation for Optical Path Monitoring: Loss Profile and Passband Narrowing EstimationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2020
- Fiber-Longitudinal Anomaly Position Identification Over Multi-Span Transmission Link Out of Receiver-end SignalsJournal of Lightwave Technology, 2020
- Self-Healing Optical Networks with Architecture on Demand NodesPublished by Institution of Engineering and Technology (IET) ,2013
- Self-Phase ModulationPublished by Elsevier BV ,2013
- Optimizing the nonlinear operator in backward propagationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- Compensation of Dispersion and Nonlinear Impairments Using Digital BackpropagationJournal of Lightwave Technology, 2008