activity
20182021
most citedOptical Fiber Communication Systems Based on End-to-End Deep Learning

8 citations · 9 across the 4 of their papers we have counts for

collaborators

5 papers

eess.SP2021

On the Comparison of Single-Carrier vs. Digital Multi-Carrier Signaling for Long-Haul Transmission of Probabilistically Shaped Constellation Formats

Kaoutar Benyahya, Amirhossein Ghazisaeidi, Vahid Aref +6

We report on theoretical and experimental investigations of the nonlinear tolerance of single carrier and digital multicarrier approaches with probabilistically shaped constellatio…

eess.SP20201 cited

Experimental Investigation of Deep Learning for Digital Signal Processing in Short Reach Optical Fiber Communications

Boris Karanov, Mathieu Chagnon, Vahid Aref +4

We investigate methods for experimental performance enhancement of auto-encoders based on a recurrent neural network (RNN) for communication over dispersive nonlinear channels. In…

eess.SP20208 cited

Optical Fiber Communication Systems Based on End-to-End Deep Learning

Boris Karanov, Mathieu Chagnon, Vahid Aref +3

We investigate end-to-end optimized optical transmission systems based on feedforward or bidirectional recurrent neural networks (BRNN) and deep learning. In particular, we report…

cs.IT2019

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…

cs.IT2018

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…