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20142026
most citedLearning computationally efficient dictionaries and their implementation as fast transforms

7 citations · 22 across the 11 of their papers we have counts for

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8 papers · 1 filter

eess.SP2026

One ISAC Array, Two Worst Cases: Hardware Impairments in Beamforming and AoA Estimation

Xuan Chen, Luc Le Magoarou

In integrated sensing and communication (ISAC), the same base-station array beamforms toward users and estimates their angle of arrival (AoA). In this paper, we study how element-l…

eess.SP2026

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…

eess.SP2023

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…

eess.SP2023

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…

eess.SP2023★ 6 cited

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…

eess.SP2023★ 2 cited

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…

eess.SP2022★ 5 cited

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…

eess.SP2020★ 2 cited

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…