7 citations · 22 across the 11 of their papers we have counts for
13 papers
Multi-dimensional hierarchical dictionary search for large MIMO-OFDM systems
Nay Klaimi, Philippe Mary, Luc Le Magoarou
Sparse recovery algorithms are of utmost importance for estimation processes in wireless communications. However, communication systems such as massive multiple input multiple outp…
Optimal blind focusing on perturbation-inducing targets in sub-unitary complex media
Jérôme Sol, Luc Le Magoarou, Philipp del Hougne
The scattering of waves in a complex medium is perturbed by polarizability changes or motion of embedded targets. These perturbations could serve as perfectly non-invasive guidesta…
Semi-Supervised End-to-End Learning for Integrated Sensing and Communications
José Miguel Mateos-Ramos, Baptiste Chatelier, Christian Häger +3
Integrated sensing and communications (ISAC) is envisioned as one of the key enablers of next-generation wireless systems, offering improved hardware, spectral, and energy efficien…
Model-based Deep Learning for High-Dimensional Periodic Structures
Lucas Polo-López, Luc Le Magoarou, Romain Contreres +1
This work presents a deep learning surrogate model for the fast simulation of high-dimensional frequency selective surfaces. We consider unit-cells which are built as multiple conc…
Model-based learning for location-to-channel mapping
Baptiste Chatelier, Luc Le Magoarou, Vincent Corlay +1
Modern communication systems rely on accurate channel estimation to achieve efficient and reliable transmission of information. As the communication channel response is highly rela…
Experimentally realized physical-model-based wave control in metasurface-programmable complex media
Jérôme Sol, Hugo Prod'homme, Luc Le Magoarou +1
The reconfigurability of radio environments with programmable metasurfaces is considered a key feature of next-generation wireless networks. Identifying suitable metasurface config…
Model-Based End-to-End Learning for Multi-Target Integrated Sensing and Communication under Hardware Impairments
José Miguel Mateos-Ramos, Christian Häger, Musa Furkan Keskin +2
We study model-based end-to-end learning in the context of integrated sensing and communication (ISAC) under hardware impairments. Hardware impairments are usually addressed by mea…
On the Tacit Linearity Assumption in Common Cascaded Models of RIS-Parametrized Wireless Channels
Antonin Rabault, Luc Le Magoarou, Jérôme Sol +4
We analytically derive from first physical principles the functional dependence of wireless channels on the RIS configuration for generic (i.e., potentially complex-scattering) RIS…
Model-Driven End-to-End Learning for Integrated Sensing and Communication
José Miguel Mateos-Ramos, Christian Häger, Musa Furkan Keskin +2
Integrated sensing and communication (ISAC) is envisioned to be one of the pillars of 6G. However, 6G is also expected to be severely affected by hardware impairments. Under such i…
Online unsupervised deep unfolding for MIMO channel estimation
Luc Le Magoarou, Stéphane Paquelet
Channel estimation is a difficult problem in MIMO systems. Using a physical model allows to ease the problem, injecting a priori information based on the physics of propagation. Ho…
Analyzing the Approximation Error of the Fast Graph Fourier Transform
Luc LeMagoarou, Nicolas Tremblay, Rémi Gribonval
The graph Fourier transform (GFT) is in general dense and requires O(n^2) time to compute and O(n^2) memory space to store. In this paper, we pursue our previous work on the approx…
Parametric channel estimation for massive MIMO
Luc Le Magoarou, Stéphane Paquelet
Channel state information is crucial to achieving the capacity of multi-antenna (MIMO) wireless communication systems. It requires estimating the channel matrix. This estimation ta…
Learning computationally efficient dictionaries and their implementation as fast transforms
Luc Le Magoarou, Rémi Gribonval
Dictionary learning is a branch of signal processing and machine learning that aims at finding a frame (called dictionary) in which some training data admits a sparse representatio…