Journal article
Inverse design of a Raman amplifier in frequency and distance domains using convolutional neural networks
Department of Photonics Engineering, Technical University of Denmark1
Machine Learning in Photonic Systems, Department of Photonics Engineering, Technical University of Denmark2
Centre of Excellence for Silicon Photonics for Optical Communications, Centers, Technical University of Denmark3
Ultra-fast Optical Communication, Department of Photonics Engineering, Technical University of Denmark4
Polytechnic University of Turin5
We present a convolutional neural network architecture for inverse Raman amplifier design. This model aims at finding the pump powers and wavelengths required for a target signal power evolution in both distance along the fiber and in frequency. Using the proposed framework, the prediction of the pump configuration required to achieve a target power profile is demonstrated numerically with high accuracy in C-band considering both counter-propagating and bidirectional pumping schemes.
For a distributed Raman amplifier based on a 100 km single-mode fiber, a low mean set (0.51, 0.54, and 0.64 dB) and standard deviation set (0.62, 0.43, and 0.38 dB) of the maximum test error are obtained numerically employing two and three counter-, and four bidirectional propagating pumps, respectively.
Language: | English |
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Year: | 2021 |
Pages: | 2650-2653 |
ISSN: | 15394794 and 01469592 |
Types: | Journal article |
DOI: | 10.1364/OL.422884 |
ORCIDs: | Soltani, Mehran , da Ros, Francesco , 0000-0001-6848-3326 and Zibar, Darko |