activity
20152021
most citedStochastic Geometry Modeling of Cellular Networks: Analysis, Simulation and Experimental Validation

38 citations · 166 across the 30 of their papers we have counts for

collaborators
Showing eess.SPShow all

14 papers · 1 filter

eess.SP2021

First experimental evaluation of ambient backscatter communications with massive MIMO reader

Romain Fara, Nada Bel-Haj-Maati, Dinh-Thuy Phan-Huy +2

Ambient backscatter communications have been introduced as low-power communications for green networking. This technology is very promising as it recycles ambient radio frequency w…

eess.SP2021

Robust Ambient Backscatter Communications with Polarization Reconfigurable Tags

Romain Fara, Dinh-Thuy Phan-Huy, Abdelwaheb Ourir +2

Ambient backscatter communication system is an emerging and promising low-energy technology for Internet of Things. In such system, a device named tag, sends a binary message to a…

eess.SP20213 cited

Learning-based Prediction, Rendering and Transmission for Interactive Virtual Reality in RIS-Assisted Terahertz Networks

Xiaonan Liu, Yansha Deng, Chong Han +1

The quality of experience (QoE) requirements of wireless Virtual Reality (VR) can only be satisfied with high data rate, high reliability, and low VR interaction latency. This high…

eess.SP2021

Intelligent Spectrum Learning for Wireless Networks with Reconfigurable Intelligent Surfaces

Bo Yang, Xuelin Cao, Chongwen Huang +3

Reconfigurable intelligent surface (RIS) has become a promising technology for enhancing the reliability of wireless communications, which is capable of reflecting the desired sign…

eess.SP20201 cited

Uplink Achievable Rate Maximization for Reconfigurable Intelligent Surface Aided Millimeter Wave Systems with Resolution-Adaptive ADCs

Yue Xiu, Jun Zhao, Ertugrul Basar +4

In this letter, we investigate the uplink of a reconfigurable intelligent surface (RIS)-aided millimeter-wave (mmWave) multi-user system. In the considered system, however, problem…

eess.SP20202 cited

MetaSensing: Intelligent Metasurface Assisted RF 3D Sensing by Deep Reinforcement Learning

Jingzhi Hu, Hongliang Zhang, Kaigui Bian +3

Using RF signals for wireless sensing has gained increasing attention. However, due to the unwanted multi-path fading in uncontrollable radio environments, the accuracy of RF sensi…