Luc Le Magoarou

Luc Le Magoarou

Associate Professor

INSA Rennes

I am an associate professor in the electronics and telecommuniciations (E&T) department at the national institute of applied sciences (INSA Rennes), France. My research interests include signal processing, machine learning and applied mathematics for efficient and frugal wireless communication systems. For a brief introduction to my research activities, see this talk.

Interests
  • Signal Processing
  • Machine Learning
  • Applied Mathematics
  • Wireless Communications
Education
  • PhD in signal and image processing, 2016

    INSA Rennes / Inria

  • MEng in telecommunications, 2013

    INSA Rennes

News

Projects

MoBAIWL
Model-Based frugal AI for efficient WireLess communication systems
MoBAIWL

Publications

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(2024). Unsupervised Learning for Gain-Phase Impairment Calibration in ISAC Systems.

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(2024). Optimal Blind Focusing on Perturbation-Inducing Targets in Sub-Unitary Complex Media. Laser & Photonics Reviews.

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(2024). Model-based learning for multi-antenna multi-frequency location-to-channel mapping.

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(2024). Optimizing Multicarrier Multiantenna Systems for LoS Channel Charting. IEEE Transactions on Wireless Communications.

Cite DOI arXiv ieeeXplore

(2024). Experimentally realized physical-model-based frugal wave control in metasurface-programmable complex media. Nature Communications.

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Students

PhD

Steve Sawadogo (PhD 2023-2026): Distributed MIMO beamforming for secure communications

Kenaz Boa (PhD 2023-2026): Efficient data processing with realistic physical models for reconfigurable intelligent surfaces

Baptiste Chatelier (PhD 2023-2026): Model-based learning for integrated sensing and communication

Taha Yassine (PhD 2020-2024): Model-based learning for channel estimation and charting

Msc

Imane Assoum (Msc 2024): Model-based deep learning for 1D passband signal interpolation

Léon Mykolyshyn (Msc 2024): Model-based deep learning for high-dimensional frequency selective surfaces synthesis

Etienne Rault (Msc 2024): Deep unfolding for channel estimation under IQ imbalance

Cheima Hammami (Msc 2024): Model-based deep learning for efficient electromagnetic modelling of high-dimensional frequency selective surfaces

Amira Bedoui (Msc 2024): Joint channel estimation and precoder design in hybrid MIMO systems