ICE seminar: EMF exposure in the evolution from current to future wireless networks
Nowadays, with the ever-increasing demand for high-speed and low-latency wireless communications, new generation of base stations, i.e., the fifth generation (5G), has been deployed recently. However, this deployment has raised growing concerns regarding the potential public health implications associated with exposure to radio-frequency electromagnetic fields (RF-EMF). According to the type of sources, RF-EMF exposure can be catergorized into uplink and downlink transmission. For the uplink, due to the increasing complexity of communication systems, it brings challenges in uplink exposure assessments. On the other hand, the advancement in downlink also requires emerging techniques, e.g., AI, to better assess the exposure level. Environmental information plus base station parameters are used to build the artificial neural network model to predict the electric field level in urban environment. In the meantime, the characterization of future cellular networks can be done using statistical methods.
Bio
Shanshan Wang is currently an assistant professor in Telecom Paris, with RFM2 team in COMELEC. She received Master degree (with Distinction) from University of Bristol in 2014. Then, she was a research engineer with the Toshiba Telecommunication Laboratory, Bristol, U.K. She received the Ph.D. degree in modeling wireless networks from L2S (CNRS), Paris-Saclay University, France, in 2019. After PhD, she worked as postdoctoral researcher in the chair C2M in Télécom Paris, on the topic of EMF exposure mapping using AI. From 2023 to 2024, she was assistant professor in the lab of ETIS in CY Cergy Paris University. She has participated several European Horizon projects, such as, 5GWireless (2015-2018), SEAWave (2022-2025), Goliat (2022-2027). Her research interests include EMF exposure characterization and AI-based prediction, stochastic geometry and system-level modeling of wireless networks, machine learning.