Luc Le Magoarou

According to our database, Luc Le Magoarou authored at least 40 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Optimizing Multicarrier Multiantenna Systems for LoS Channel Charting.

Taha Yassine, Luc Le Magoarou, Matthieu Crussière, Stéphane Paquelet

IEEE Trans. Wirel. Commun., October, 2024

On the Tacit Linearity Assumption in Common Cascaded Models of RIS-Parametrized Wireless Channels.

Antonin Rabault, Luc Le Magoarou, Jérôme Sol, George C. Alexandropoulos, Nir Shlezinger, H. Vincent Poor, Philipp del Hougne

IEEE Trans. Wirel. Commun., August, 2024

Efficient Frequency Selective Surface Analysis via End-to-End Model-Based Learning.

Cheima Hammami, Lucas Polo-López, Luc Le Magoarou

CoRR, 2024

Model-based learning for multi-antenna multi-frequency location-to-channel mapping.

Baptiste Chatelier, Vincent Corlay, Matthieu Crussière, Luc Le Magoarou

CoRR, 2024

Model-Based Learning for Location-to-Channel Mapping.

Baptiste Chatelier, Luc Le Magoarou, Vincent Corlay, Matthieu Criissière

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

Model-based Deep Learning for High-Dimensional Periodic Structures.

Lucas Polo-López, Luc Le Magoarou, Romain Contreres, María García-Vigueras

CoRR, 2023

Model-based learning for location-to-channel mapping.

Baptiste Chatelier, Luc Le Magoarou, Vincent Corlay, Matthieu Crussière

CoRR, 2023

Model-Driven End-to-End Learning for Integrated Sensing and Communication.

José Miguel Mateos-Ramos, Christian Häger, Musa Furkan Keskin, Luc Le Magoarou, Henk Wymeersch

Proceedings of the IEEE International Conference on Communications, 2023

Efficient Deep Unfolding for SISO-OFDM Channel Estimation.

Baptiste Chatelier, Luc Le Magoarou, Getachew Redieteab

Proceedings of the IEEE International Conference on Communications, 2023

Model-Based Deep Learning for Beam Prediction Based on a Channel Chart.

Taha Yassine, Baptiste Chatelier, Vincent Corlay, Matthieu Crussière, Stéphane Paquelet, Olav Tirkkonen, Luc Le Magoarou

Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

2022

mpNet: Variable Depth Unfolded Neural Network for Massive MIMO Channel Estimation.

Taha Yassine, Luc Le Magoarou

IEEE Trans. Wirel. Commun., 2022

Pervasive Artificial Intelligence in Next Generation Wireless: The Hexa-X Project Perspective.

Miltiadis C. Filippou, Vasiliki Lamprousi, Jafar Mohammadi, Mattia Merluzzi, Elif Ustundag Soykan, Tamás Borsos, Nandana Rajatheva, Nuwanthika Rajapaksha, Luc Le Magoarou, Pietro Piscione, András Benczúr, Quentin Lampin, Guillaume Larue, Dani Korpi, Pietro Ducange, Alessandro Renda, Hamed Farhadi, Johan Haraldson, Leonardo Gomes Baltar, Emilio Calvanese Strinati, Panagiotis Demestichas, Emrah Tomur

Proceedings of the Short Paper Proceedings of the First International Workshop on Artificial Intelligence in Beyond 5G and 6G Wireless Networks (AI6G 2022) co-located with IEEE World Congress on Computational Intelligence (WCCI2022), 2022

Leveraging triplet loss and nonlinear dimensionality reduction for on-the-fly channel charting.

Taha Yassine, Luc Le Magoarou, Stéphane Paquelet, Matthieu Crussière

Proceedings of the 23rd IEEE International Workshop on Signal Processing Advances in Wireless Communication, 2022

Deep Learning for Location Based Beamforming with Nlos Channels.

Luc Le Magoarou, Taha Yassine, Stéphane Paquelet, Matthieu Crussière

Proceedings of the IEEE International Conference on Acoustics, 2022

Channel charting based beamforming.

Luc Le Magoarou, Taha Yassine, Stéphane Paquelet, Matthieu Crussière

Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

2021

Efficient Channel Charting via Phase-Insensitive Distance Computation.

Luc Le Magoarou

IEEE Wirel. Commun. Lett., 2021

Similarity-Based Prediction for Channel Mapping and User Positioning.

Luc Le Magoarou

IEEE Commun. Lett., 2021

2020

Channel Estimation: Unified View of Optimal Performance and Pilot Sequences.

Luc Le Magoarou, Stéphane Paquelet

IEEE Trans. Signal Process., 2020

On the Computation of Integrals of Bivariate Gaussian Distribution.

Vincent Savaux, Luc Le Magoarou

Proceedings of the IEEE Symposium on Computers and Communications, 2020

2019

Performance of MIMO channel estimation with a physical model.

Luc Le Magoarou, Stéphane Paquelet

CoRR, 2019

Exploiting the Massive MIMO Channel Structural Properties for Minimization of Channel Estimation Error and Training Overhead.

Samer Bazzi, Stelios Stefanatos, Luc Le Magoarou, Salah Eddine Hajri, Mohamad Assaad, Stéphane Paquelet, Gerhard Wunder, Wen Xu

IEEE Access, 2019

Massive MIMO Channel Estimation taking into account spherical waves.

Luc Le Magoarou, Antoine Le Calvez, Stéphane Paquelet

Proceedings of the 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2019

2018

Approximate Fast Graph Fourier Transforms via Multilayer Sparse Approximations.

Luc Le Magoarou, Rémi Gribonval, Nicolas Tremblay

IEEE Trans. Signal Inf. Process. over Networks, 2018

Bias-variance tradeoff in MIMO channel estimation.

Luc Le Magoarou, Stéphane Paquelet

CoRR, 2018

MIMO Channel Hardening: A Physical Model based Analysis.

Matthieu Roy, Stéphane Paquelet, Luc Le Magoarou, Matthieu Crussière

CoRR, 2018

MIMO Channel Hardening for Ray-based Models.

Matthieu Roy, Stéphane Paquelet, Luc Le Magoarou, Matthieu Crussière

Proceedings of the 14th International Conference on Wireless and Mobile Computing, 2018

Parametric Channel Estimation for Massive MIMO.

Luc Le Magoarou, Stéphane Paquelet

Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018

2017

Analyzing the approximation error of the fast graph Fourier transform.

Luc Le Magoarou, Nicolas Tremblay, Rémi Gribonval

Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

2016

Matrices efficientes pour le traitement du signal et l'apprentissage automatique. (Efficient matrices for signal processing and machine learning).

Luc Le Magoarou

PhD thesis, 2016

Flexible Multilayer Sparse Approximations of Matrices and Applications.

Luc Le Magoarou, Rémi Gribonval

IEEE J. Sel. Top. Signal Process., 2016

Approximate Fast Fourier Transforms on graphs via multi-layer sparse approximations.

Luc Le Magoarou, Rémi Gribonval, Nicolas Tremblay

CoRR, 2016

Are there approximate fast fourier transforms on graphs?

Luc Le Magoarou, Rémi Gribonval

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

2015

Text-Informed Audio Source Separation. Example-Based Approach Using Non-Negative Matrix Partial Co-Factorization.

Luc Le Magoarou, Alexey Ozerov, Ngoc Q. K. Duong

J. Signal Process. Syst., 2015

Flexible Multi-layer Sparse Approximations of Matrices and Applications.

Luc Le Magoarou, Rémi Gribonval

CoRR, 2015

Chasing butterflies: In search of efficient dictionaries.

Luc Le Magoarou, Rémi Gribonval

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

FAμST: Speeding up linear transforms for tractable inverse problems.

Luc Le Magoarou, Rémi Gribonval, Alexandre Gramfort

Proceedings of the 23rd European Signal Processing Conference, 2015

2014

Learning computationally efficient dictionaries and their implementation as fast transforms.

Luc Le Magoarou, Rémi Gribonval

CoRR, 2014

Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14).

Laurent Jacques, Christophe De Vleeschouwer, Yannick Boursier, Prasad Sudhakar, C. De Mol, Aleksandra Pizurica, Sandrine Anthoine, Pierre Vandergheynst, Pascal Frossard, Cagdas Bilen, Srdan Kitic, Nancy Bertin, Rémi Gribonval, Nicolas Boumal, Bamdev Mishra, Pierre-Antoine Absil, Rodolphe Sepulchre, Shaun Bundervoet, Colas Schretter, Ann Dooms, Peter Schelkens, Olivier Chabiron, François Malgouyres, Jean-Yves Tourneret, Nicolas Dobigeon, Pierre Chainais, Cédric Richard, Bruno Cornelis, Ingrid Daubechies, David B. Dunson, Marie Danková, Pavel Rajmic, Kévin Degraux, Valerio Cambareri, Bert Geelen, Gauthier Lafruit, Gianluca Setti, Jean-François Determe, Jérôme Louveaux, François Horlin, Angélique Drémeau, Patrick Héas, Cédric Herzet, Vincent Duval, Gabriel Peyré, Alhussein Fawzi, Mike E. Davies, Nicolas Gillis, Stephen A. Vavasis, Charles Soussen, Luc Le Magoarou, Jingwei Liang, Jalal Fadili, Antoine Liutkus, David Martina, Sylvain Gigan, Laurent Daudet, Mauro Maggioni, Stanislav Minsker, Nate Strawn, C. Mory, Fred Maurice Ngolè Mboula, Jean-Luc Starck, Ignace Loris, Samuel Vaiter, Mohammad Golbabaee, Dejan Vukobratovic

CoRR, 2014

2013

Text-informed audio source separation using nonnegative matrix partial co-factorization.

Luc Le Magoarou, Alexey Ozerov, Ngoc Q. K. Duong

Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2013

Maximum likelihood estimation of clutter subspace in non homogeneous noise context.

Arnaud Breloy, Luc Le Magoarou, Guillaume Ginolhac, Frédéric Pascal, Philippe Forster

Proceedings of the 21st European Signal Processing Conference, 2013