100 citations · 131 across the 10 of their papers we have counts for
6 papers · 1 filter
Geometric Shaping of 2-Dimensional Constellations in the Presence of Laser Phase Noise
Hubert Dzieciol, Gabriele Liga, Eric Sillekens +2
In this paper, we propose a geometric shaping (GS) strategy to design 8, 16, 32 and 64-ary modulation formats for the optical fibre channel impaired by both additive white Gaussian…
Concept and Experimental Demonstration of Optical IM/DD End-to-End System Optimization using a Generative Model
Boris Karanov, Mathieu Chagnon, Vahid Aref +3
We perform an experimental end-to-end transceiver optimization via deep learning using a generative adversarial network to approximate the test-bed channel. Previously, optimizatio…
Deep Learning for Communication over Dispersive Nonlinear Channels: Performance and Comparison with Classical Digital Signal Processing
Boris Karanov, Gabriele Liga, Vahid Aref +3
In this paper, we apply deep learning for communication over dispersive channels with power detection, as encountered in low-cost optical intensity modulation/direct detection (IM/…
End-to-End Optimized Transmission over Dispersive Intensity-Modulated Channels Using Bidirectional Recurrent Neural Networks
Boris Karanov, Domaniç Lavery, Polina Bayvel +1
We propose an autoencoding sequence-based transceiver for communication over dispersive channels with intensity modulation and direct detection (IM/DD), designed as a bidirectional…
Experimental Demonstration of Geometrically-Shaped Constellations Tailored to the Nonlinear Fibre Channel
E. Sillekens, D. Semrau, D. Lavery +2
A geometrically-shaped 256-QAM constellation, tailored to the nonlinear optical fibre channel, is experimentally demonstrated. The proposed constellation outperforms both uniform a…
End-to-end Deep Learning of Optical Fiber Communications
Boris Karanov, Mathieu Chagnon, Félix Thouin +5
In this paper, we implement an optical fiber communication system as an end-to-end deep neural network, including the complete chain of transmitter, channel model, and receiver. Th…