My Research
RF-EMF Exposure in Downlink and Uplink Networks
The risk perception of electronic-magnetic field (EMF) exposure is nowadays a hot issue with the fast development of wireless communications. Usually, RF-EMF monitoring is often carried out using “one-time” measurement campaigns. Measurement equipment includes spectrum analyzers, exposimeters, and network-based mobile phone tools. The monitoring can also be done using fixed sensors installed and tested in cities such as Paris. Besides in situ measurements, statistical methods, e.g., ray-based simulators, and Kriging, are used in assessing EMF exposure. In this work, we did assessments and forecasting of EMF exposure for both outdoor and indoor environments by using ANN based on data collected by simulations, sensors measurements, network-based measurements.
- 2024 "Assessment of EMF Exposure Induced by Wireless Cellular Phones in Various Usage Scenarios in France" - PDF
- 2024 "Statistical Analysis of RF-EMF Exposure Induced by Cellular Wireless Networks in Public Transportation Facilities of the Paris Region" - PDF
- 2024 "Assessment of Radio Frequency Electromagnetic Field Exposure Induced by Base Stations in Several Micro-Environments in France" - PDF
- 2023 "Impact of Indoor Distributed Antenna System on RF-EMF Global Exposure" - PDF
- 2023 "An extrapolation approach for RF-EMF exposure prediction in an urban area using artificial neural network" - PDF
- 2023 "Statistical characterization and modeling of indoor RF-EMF down-link exposure" - PDF
- 2022 "Prediction of RF-EMF exposure by outdoor drive test measurements" - PDF
- 2021 "Artificial neural network-based uplink power prediction from multi-floor indoor measurement campaigns in 4G networks" - PDF
- 2020 "Sensor-aided EMF exposure assessments in an urban environment using artificial neural networks" - PDF
Stochastic Geomrety based Modelling Wireless Networks
The performance of wireless networks is fundamentally limited by aggregate interference, which depends on the spatial distributions of the interferers, channel conditions, and user traffic patterns. Empirical evidence suggests, however, that practical cellular network deployments are likely to exhibit some degree of interactions among the locations of the BSs, which include spatial inhibition, i.e., repulsion, and spatial clustering. Conventional Poisson point process based approaches are not sufficient anymore. For this, accurate system-level performance characterization and evaluation with spatio-temporal correlation are required. In this project, we studied the performance of spatially-correlated cellular networks, including coverage probability, MISR, Meta distribution, and aggregate average rate under a multi-operator sharing scenario.
- 2024 "Joint metrics for EMF exposure and coverage in real-world homogeneous and inhomogeneous cellular networks" - PDF
- 2020 "A statistical estimation of 5G massive MIMO networks’ exposure using stochastic geometry in mmWave bands" - PDF
- 2019 "On the meta distribution in spatially correlated non-Poisson cellular networks" - PDF
- 2019 "On the mean interference-to-signal ratio in spatially correlated cellular networks"
- 2018 "Inhomogeneous double thinning—Modeling and analysis of cellular networks by using inhomogeneous Poisson point processes" - PDF