108 citations · 363 across the 21 of their papers we have counts for
6 papers · 1 filter
Flexible Raman Amplifier Optimization Based on Machine Learning-aided Physical Stimulated Raman Scattering Model
Metodi Plamenov Yankov, Francesco Da Ros, Uiara Celine de Moura +2
The problem of Raman amplifier optimization is studied. A differentiable interpolation function is obtained for the Raman gain coefficient using machine learning (ML), which allows…
Spectral and spatial power evolution design with machine learning-enabled Raman amplification
Mehran Soltani, Francesco Da Ros, Andrea Carena +1
We present a machine learning (ML) framework for designing desired signal power profiles over the spectral and spatial domains in the fiber span. The proposed framework adjusts the…
A GN/EGN-Model Real-Time Closed-Form Formula Tested over 7,000 Virtual Links
Mahdi Ranjbar Zefreh, Andrea Carena, Fabrizio Forghieri +2
We derived a fully-closed-form GN-model formula and tested its accuracy of over 7,000 highly randomized Cband system scenarios. By further applying a correction that leverages the…
High-Capacity and Rain-Resilient Free-Space Optics Link Enabled by Time-Adaptive Probabilistic Shaping
F. P. Guiomar, A. Lorences-Riesgo, D. Ranzal +6
Using time-adaptive probabilistic shaped 64QAM driven by a simple SNR prediction algorithm, we demonstrate 450 Gbps transmission over a 55-m free-space optics link with enhanced…
Observing the Effect of Polarization Mode Dispersion on Nonlinear Interference Generation in Wide-Band Optical Links
Dario Pilori, Mattia Cantono, Alessio Ferrari +2
With the extension of the spectral exploitation of optical fibers beyond the C-band, accurate modeling and simulation of nonlinear interference (NLI) generation is of the utmost pe…
An ultra-fast method for gain and noise prediction of Raman amplifiers
Ann Margareth Rosa Brusin, Vittorio Curri, Darko Zibar +1
A machine learning method for prediction of Raman gain and noise spectra is presented: it guarantees high-accuracy (RMSE < 0.4 dB) and low computational complexity making it suitab…