Indoor genetic algorithm-based 5G network planning using a machine learning model for path loss estimation

Y Hervis Santana, R Martinez Alonso, G Guillen Nieto… - Applied Sciences, 2022 - mdpi.com
Accurate wireless network planning is crucial for the deployment of new wireless services.
This usually requires the consecutive evaluation of many candidate solutions, which is only …

Prediction of RF-EMF exposure by outdoor drive test measurements

S Wang, T Mazloum, J Wiart - Telecom, 2022 - mdpi.com
In this paper, we exploit the artificial neural network (ANN) model for a spatial reconstruction
of radio-frequency (RF) electromagnetic field (EMF) exposure in an outdoor urban …

Survey of exposure to RF electromagnetic fields in the connected car

G Tognola, M Bonato, M Benini, S Aerts… - IEEE …, 2022 - ieeexplore.ieee.org
Future vehicles will be increasingly connected to enable new applications and improve
safety, traffic efficiency and comfort, through the use of several wireless access technologies …

A generalizable indoor propagation model based on graph neural networks

S Liu, T Onishi, M Taki… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
A surrogate model that “learns” the physics of radio wave propagation is indispensable for
the efficient optimization of communication network coverages and comprehensive …

An Exposimetric Electromagnetic Comparison of Mobile Phone Emissions: 5G versus 4G Signals Analyses by Means of Statistics and Convolutional Neural Networks …

S Miclaus, DB Deaconescu, D Vatamanu, AM Buda - Technologies, 2023 - mdpi.com
To gain a deeper understanding of the hotly contested topic of the non-thermal biological
effects of microwaves, new metrics and methodologies need to be adopted. The direction …

Artificial neural network-based uplink power prediction from multi-floor indoor measurement campaigns in 4G networks

T Mazloum, S Wang, M Hamdi… - Frontiers in Public …, 2021 - frontiersin.org
Paving the path toward the fifth generation (5G) of wireless networks with a huge increase in
the number of user equipment has strengthened public concerns on human exposure to …

EME-CNTK: Infinite Limits of Convolutional Neural Network for Urban Electromagnetic Field Exposure Reconstruction

M Mallik, B Allaert, E Egea-Lopez, DP Gaillot… - IEEE …, 2024 - ieeexplore.ieee.org
Electromagnetic field exposure (EMF) has grown to be a critical concern as a consequence
of the ongoing installation of fifth-generation cellular networks (5G). The lack of …

Performance and EMF exposure trade-offs in human-centric cell-free networks

F Malandrino, E Chiaramello… - … on Modeling and …, 2022 - ieeexplore.ieee.org
In cell-free wireless networks, multiple connectivity options and technologies are available to
serve each user. Traditionally, such options are ranked and selected solely based on the …

Physics-Informed Machine Learning Modelling of RF-EMF Exposure in Massive MIMO Systems

S Bilson, TH Loh, F Héliot, A Thompson - IEEE Access, 2024 - ieeexplore.ieee.org
Beamforming and massive multiple-input-multiple-output (mMIMO) technologies are key
features of base stations (BSs) in the fifth-generation (5G) of mobile networks. This …

On the Quasistationarity of the Ambient Electromagnetic Field Generated by Wi-Fi Sources

L Tuță, G Roșu, A Andone, S Spandole-Dinu… - Electronics, 2024 - mdpi.com
In recent decades, the widespread use of mobile phones and wireless technologies has led
to a significant increase in radiofrequency electromagnetic fields (RF-EMFs), raising …