150 citations · 875 across the 67 of their papers we have counts for
8 papers · 1 filter
Reservoir Computing-based Multi-Symbol Equalization for PAM 4 Short-reach Transmission
Yevhenii Osadchuk, Ognjen Jovanovic, Darko Zibar +1
We propose spectrum-sliced reservoir computer-based (RC) multi-symbol equalization for 32-GBd PAM4 transmission. RC with 17 symbols at the output achieves an order of magnitude red…
Data-efficient Modeling of Optical Matrix Multipliers Using Transfer Learning
Ali Cem, Ognjen Jovanovic, Siqi Yan +3
We demonstrate transfer learning-assisted neural network models for optical matrix multipliers with scarce measurement data. Our approach uses <10\% of experimental data needed for…
Geometric Constellation Shaping for Fiber-Optic Channels via End-to-End Learning
Ognjen Jovanovic, Francesco Da Ros, Darko Zibar +1
End-to-end learning has become a popular method to optimize a constellation shape of a communication system. When the channel model is differentiable, end-to-end learning can be ap…
Data-driven Modeling of Mach-Zehnder Interferometer-based Optical Matrix Multipliers
Ali Cem, Siqi Yan, Yunhong Ding +2
Photonic integrated circuits are facilitating the development of optical neural networks, which have the potential to be both faster and more energy efficient than their electronic…
Experimental validation of machine-learning based spectral-spatial power evolution shaping using Raman amplifiers
Mehran Soltani, Francesco Da Ros, Andrea Carena +1
We experimentally validate a real-time machine learning framework, capable of controlling the pump power values of Raman amplifiers to shape the signal power evolution in two-dimen…
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…
Experimental Validation of Spectral-Spatial Power Evolution Design Using Raman Amplifiers
Mehran Soltani, Francesco Da Ros, Andrea Carena +1
We experimentally validate a machine learning-enabled Raman amplification framework, capable of jointly shaping the signal power evolution in two domains: frequency and fiber dista…
Capacity and Achievable Rates of Fading Few-mode MIMO IM/DD Optical Fiber Channels
Metodi P. Yankov, Francesco Da Ros, Søren Forchhammer +1
The optical fiber multiple-input multiple-output (MIMO) channel with intensity modulation and direct detection (IM/DD) per spatial path is treated. The spatial dimensions represent…