Journal article · Preprint article
Simultaneous gain profile design and noise figure prediction for Raman amplifiers using machine learning
Department of Photonics Engineering, Technical University of Denmark1
Machine Learning in Photonic Systems, Department of Photonics Engineering, Technical University of Denmark2
Polytechnic University of Turin3
Centre of Excellence for Silicon Photonics for Optical Communications, Centers, Technical University of Denmark4
A machine learning framework predicting pump powers and noise figure profile for a target distributed Raman amplifier gain profile is experimentally demonstrated. We employ a single-layer neural network to learn the mapping from the gain profiles to the pump powers and noise figures. The obtained results show highly accurate gain profile designs and noise figure predictions, with a maximum error on average of ∼ 0.3 dB.
This framework provides a comprehensive characterization of the Raman amplifier and thus is a valuable tool for predicting the performance of next-generation optical communication systems, expected to employ Raman amplification.
| Language: | English |
|---|---|
| Year: | 2021 |
| Pages: | 1157-1160 |
| ISSN: | 15394794 and 01469592 |
| Types: | Journal article and Preprint article |
| DOI: | 10.1364/OL.417243 |
| ORCIDs: | de Moura, Uiara Celine , Zibar, Darko , da Ros, Francesco , 0000-0002-3711-9350 and 0000-0001-6848-3326 |
