Generation of electromagnetic exposure maps for 5G communications

  1. Esteban Egea-Lopez 1
  2. Mohammed Mallik
  3. Laurent Clavier
  4. Davy P. Gaillot
  1. 1 Universidad Politécnica de Cartagena
    info

    Universidad Politécnica de Cartagena

    Cartagena, España

    ROR https://ror.org/02k5kx966

Konferenzberichte:
18th European Conference on Antennas and Propagation ( EuCAP2024): Glasgow, del 17 al 22 de marzo de 2024

Verlag: IEEE

ISBN: 978-88-31299-09-1

Datum der Publikation: 2023

Art: Konferenz-Beitrag

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Zusammenfassung

Monitoring human exposure to electro magnetic field sources is a growing concern. An approach for the evaluation of exposure is the generation of radio-frequency electro-magnetic fields (RF EMF) exposure mapsvia simulation, which is complex due to the need to simulate the multiple sources involved. As an alternative, it has been explored the automatic generation of EMF exposure maps by machine learning (ML) methodsusing as input the measurements from sensors located in the area of interest. These methods, due to the scarcity of measurements, still require simulation for generating the dataset for training the algorithms. In thispaper we describe how to generate exposure maps for 5G networks with our ray-tracing tool Opal, to generate a large number of EMF maps that can be used to train ML algorithms. We describe how we generatethem without the need to execute demanding higher level simulations whose details are not necessary.