Search Results for author: Jean-Marie Gorce

Found 8 papers, 0 papers with code

Indoor Localization of Smartphones Thanks to Zero-Energy-Devices Beacons

no code implementations26 Feb 2024 Shanglin Yang, Yohann Benedic, Dinh-Thuy Phan-Huy, Jean-Marie Gorce, Guillaume Villemaud

We accurately simulate the ambient waves from a BS of Orange 4G commercial network, inside an existing large building covered with ZED beacons, thanks to a ray-tracing-based propagation simulation tool.

Indoor Localization

Scalable Joint Learning of Wireless Multiple-Access Policies and their Signaling

no code implementations8 Jun 2022 Mateus P. Mota, Alvaro Valcarce, Jean-Marie Gorce

In this paper, we apply an multi-agent reinforcement learning (MARL) framework allowing the base station (BS) and the user equipments (UEs) to jointly learn a channel access policy and its signaling in a wireless multiple access scenario.

Multi-agent Reinforcement Learning reinforcement-learning +1

Learning OFDM Waveforms with PAPR and ACLR Constraints

no code implementations21 Oct 2021 Mathieu Goutay, Fayçal Ait Aoudia, Jakob Hoydis, Jean-Marie Gorce

An attractive research direction for future communication systems is the design of new waveforms that can both support high throughputs and present advantageous signal characteristics.

The Emergence of Wireless MAC Protocols with Multi-Agent Reinforcement Learning

no code implementations16 Aug 2021 Mateus P. Mota, Alvaro Valcarce, Jean-Marie Gorce, Jakob Hoydis

In this paper, we propose a new framework, exploiting the multi-agent deep deterministic policy gradient (MADDPG) algorithm, to enable a base station (BS) and user equipment (UE) to come up with a medium access control (MAC) protocol in a multiple access scenario.

Multi-agent Reinforcement Learning reinforcement-learning +1

Machine Learning-enhanced Receive Processing for MU-MIMO OFDM Systems

no code implementations30 Jun 2021 Mathieu Goutay, Fayçal Ait Aoudia, Jakob Hoydis, Jean-Marie Gorce

Machine learning (ML) can be used in various ways to improve multi-user multiple-input multiple-output (MU-MIMO) receive processing.

BIG-bench Machine Learning

End-to-End Learning of OFDM Waveforms with PAPR and ACLR Constraints

no code implementations30 Jun 2021 Mathieu Goutay, Fayçal Ait Aoudia, Jakob Hoydis, Jean-Marie Gorce

Orthogonal frequency-division multiplexing (OFDM) is widely used in modern wireless networks thanks to its efficient handling of multipath environment.

Machine Learning for MU-MIMO Receive Processing in OFDM Systems

no code implementations15 Dec 2020 Mathieu Goutay, Fayçal Ait Aoudia, Jakob Hoydis, Jean-Marie Gorce

Machine learning (ML) starts to be widely used to enhance the performance of multi-user multiple-input multiple-output (MU-MIMO) receivers.

BIG-bench Machine Learning

Transmitter Classification With Supervised Deep Learning

no code implementations20 May 2019 Cyrille Morin, Leonardo Cardoso, Jakob Hoydis, Jean-Marie Gorce, Thibaud Vial

Hardware imperfections in RF transmitters introduce features that can be used to identify a specific transmitter amongst others.

Classification General Classification

Cannot find the paper you are looking for? You can Submit a new open access paper.