Gain Design of Few-Mode Fiber Raman Amplifiers Using an Autoencoder-Based Machine Learning Approach

Marcon G.
Galtarossa A.
Palmieri L.
Santagiustina M.

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Publication date

January 2020

DOI

10.1109/ECOC48923.2020.9333401

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Abstract

We propose an unsupervised machine learning method based on autoencoders to design the gain profile of few-mode-fiber Raman amplifiers. We test the method for flat and tilted profiles across the C+L optical band, using a few-mode fiber supporting 6 LP mode groups

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Gain Design of Few-Mode Fiber Raman Amplifiers Using an Autoencoder-Based Machine Learning Approach

Abstract

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Gain Design of Few-Mode Fiber Raman Amplifiers Using an Autoencoder-Based Machine Learning Approach

Abstract

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