108 citations · 363 across the 21 of their papers we have counts for
5 papers · 1 filter
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…
Experimental demonstration of arbitrary Raman gain-profile designs using machine learning
Uiara C. de Moura, Francesco Da Ros, A. Margareth Rosa Brusin +2
A machine learning framework for Raman amplifier design is experimentally tested. Performance in terms of maximum error over the gain profile is investigated for various fiber type…
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…