5 papers
Base Station Deployment under EMF constrain by Deep Reinforcement learning
Mohammed Mallik, Guillaume Villemaud
As 5G networks rapidly expand and 6G technologies emerge, characterized by dense deployments, millimeter-wave communications, and dynamic beamforming, the need for scalable simulat…
Neyman Pearson Detector for Multiple Ambient Backscatter Zero-Energy-Devices Beacons using Near-Perfect Code
Shanglin Yang, Jean-Marie Gorce, Muhammad Jehangir Khan +2
Recently, a novel ultra-low-power indoor localization system based on Zero-Energy Devices (ZEDs) has shown promising results in ambient backscatter communication. In this paper, we…
Neyman-Pearson Detector for Ambient Backscatter Zero-Energy-Devices Beacons
Shanglin Yang, Jean-Marie Gorce, Muhammad Jehangir Khan +2
Recently, a novel ultra-low power indoor wireless positioning system has been proposed. In this system, Zero-Energy-Devices (ZED) beacons are deployed in Indoor environments, and l…
Channel Estimation by Infinite Width Convolutional Networks
Mohammed Mallik, Guillaume Villemaud
In wireless communications, estimation of channels in OFDM systems spans frequency and time, which relies on sparse collections of pilot data, posing an ill-posed inverse problem.…
Indoor Localization of Smartphones Thanks to Zero-Energy-Devices Beacons
Shanglin Yang, Yohann Benedic, Dinh-Thuy Phan-Huy +2
In this paper, we present a new ultra-low power method of indoor localization of smartphones (SM) based on zero-energy-devices (ZEDs) beacons instead of active wireless beacons. Ea…