429 citations · 441 across the 7 of their papers we have counts for
7 papers
Efficient Training of Volterra Series-Based Pre-distortion Filter Using Neural Networks
Vinod Bajaj, Mathieu Chagnon, Sander Wahls +1
We present a simple, efficient "direct learning" approach to train Volterra series-based digital pre-distortion filters using neural networks. We show its superior performance over…
End-to-End Learning of Joint Geometric and Probabilistic Constellation Shaping
Vahid Aref, Mathieu Chagnon
We present a novel autoencoder-based learning of joint geometric and probabilistic constellation shaping for coded-modulation systems. It can maximize either the mutual information…
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…
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…
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…
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…
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…