Forward Raman Amplifier Optimization Using Machine Learning-aided Physical Modeling
Author:
Affiliation:
1. Technical University of Denmark,Department of Photonics Engineering,Lyngby,Denmark
2. Politecnico di Torino,Dipartimento di Elettronica e Telecomunicazioni,Torino,Italy,10129
Funder
European Research Council (ERC-CoG FRECOM)
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9849706/9849712/09849857.pdf?arnumber=9849857
Reference11 articles.
1. Inverse design of a Raman amplifier in frequency and distance domains using convolutional neural networks
2. Model-Aware Deep Learning Method for Raman Amplification in Few-Mode Fibers
3. Unrepeatered Optical Systems Design based on Iterative Channel Pre-Emphasis Optimization
4. Channel Power Optimization of WDM Systems Following Gaussian Noise Nonlinearity Model in Presence of Stimulated Raman Scattering
5. GNPy: an open source application for physical layer aware open optical networks
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1. Model-Aware XGBoost Method Towards Optimum Performance of Flexible Distributed Raman Amplifier;IEEE Photonics Journal;2023-08
2. Ultra-Wideband WDM Transmission Based on Multistage Raman Amplification;2023 Opto-Electronics and Communications Conference (OECC);2023-07-02
3. Flexible Raman Amplifier Optimization Based on Machine Learning-Aided Physical Stimulated Raman Scattering Model;Journal of Lightwave Technology;2023-01-15
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