3 papers
eess.SP2022
Model-Based Deep Learning of Joint Probabilistic and Geometric Shaping for Optical Communication
Vladislav Neskorniuk, Andrea Carnio, Domenico Marsella +3
Autoencoder-based deep learning is applied to jointly optimize geometric and probabilistic constellation shaping for optical coherent communication. The optimized constellation sha…
eess.SP2021
End-to-End Deep Learning of Long-Haul Coherent Optical Fiber Communications via Regular Perturbation Model
Vladislav Neskorniuk, Andrea Carnio, Vinod Bajaj +4
We present a novel end-to-end autoencoder-based learning for coherent optical communications using a "parallelizable" perturbative channel model. We jointly optimized constellation…
cs.IT2018
Nonlinearity Mitigation in WDM Systems: Models, Strategies, and Achievable Rates
Marco Secondini, Erik Agrell, Enrico Forestieri +2
After reviewing models and mitigation strategies for interchannel nonlinear interference (NLI), we focus on the frequency-resolved logarithmic perturbation model to study the coher…