A Stochastic Geometry Approach to EMF Exposure Modeling
Downlink exposure to electromagnetic fields due to cellular base stations in urban environments is studied using the stochastic geometry framework. A two-dimensional Poisson Point Process is assumed for the base station distribution. Mathematical expressions of statistics of exposure are derived fro...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9462948/ |
| _version_ | 1811274192753000448 |
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| author | Quentin Gontier Lucas Petrillo Francois Rottenberg Francois Horlin Joe Wiart Claude Oestges Philippe De Doncker |
| author_facet | Quentin Gontier Lucas Petrillo Francois Rottenberg Francois Horlin Joe Wiart Claude Oestges Philippe De Doncker |
| author_sort | Quentin Gontier |
| collection | DOAJ |
| description | Downlink exposure to electromagnetic fields due to cellular base stations in urban environments is studied using the stochastic geometry framework. A two-dimensional Poisson Point Process is assumed for the base station distribution. Mathematical expressions of statistics of exposure are derived from a simple propagation model taking into account the height of the base stations. The error on exposure made by taking a limited number of base stations, instead of the whole set, is quantified. The relative impact of the model parameters on the statistics of exposure is highlighted. The method is then applied and the model parameters are calibrated using experimental data obtained by drive-tests in two Brussels municipalities, in Belgium, for the 2100 MHz and 2600 MHz frequency bands. It is shown that the proposed model fits experimental values, paving the way to a new methodology to assess general public exposure to electromagnetic fields, for any frequency band. An insight is given on how to apply the methodology to a real case without access to experimental data. |
| first_indexed | 2024-04-12T23:14:32Z |
| format | Article |
| id | doaj.art-02930bd368d740bd937a72d6d4ba5a07 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-12T23:14:32Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-02930bd368d740bd937a72d6d4ba5a072022-12-22T03:12:43ZengIEEEIEEE Access2169-35362021-01-019917779178710.1109/ACCESS.2021.30918049462948A Stochastic Geometry Approach to EMF Exposure ModelingQuentin Gontier0https://orcid.org/0000-0003-2490-5608Lucas Petrillo1Francois Rottenberg2https://orcid.org/0000-0002-2150-8511Francois Horlin3https://orcid.org/0000-0001-5790-7031Joe Wiart4Claude Oestges5https://orcid.org/0000-0002-0902-4565Philippe De Doncker6https://orcid.org/0000-0003-0187-575XWireless Communications Group, Université libre de Bruxelles, Brussels, BelgiumBrussels Environment, Brussels, BelgiumESAT-DRAMCO, Ghent Technology Campus, KU Leuven, Ghent, BelgiumWireless Communications Group, Université libre de Bruxelles, Brussels, BelgiumChaire C2M, LTCI, Telecom Paris, Institut Polytechnique de Paris, Palaiseau, FranceICTEAM Institute, Université catholique de Louvain, Louvain-la-Neuve, BelgiumWireless Communications Group, Université libre de Bruxelles, Brussels, BelgiumDownlink exposure to electromagnetic fields due to cellular base stations in urban environments is studied using the stochastic geometry framework. A two-dimensional Poisson Point Process is assumed for the base station distribution. Mathematical expressions of statistics of exposure are derived from a simple propagation model taking into account the height of the base stations. The error on exposure made by taking a limited number of base stations, instead of the whole set, is quantified. The relative impact of the model parameters on the statistics of exposure is highlighted. The method is then applied and the model parameters are calibrated using experimental data obtained by drive-tests in two Brussels municipalities, in Belgium, for the 2100 MHz and 2600 MHz frequency bands. It is shown that the proposed model fits experimental values, paving the way to a new methodology to assess general public exposure to electromagnetic fields, for any frequency band. An insight is given on how to apply the methodology to a real case without access to experimental data.https://ieeexplore.ieee.org/document/9462948/Cellular networksexposurePoisson Point Processstochastic geometry |
| spellingShingle | Quentin Gontier Lucas Petrillo Francois Rottenberg Francois Horlin Joe Wiart Claude Oestges Philippe De Doncker A Stochastic Geometry Approach to EMF Exposure Modeling IEEE Access Cellular networks exposure Poisson Point Process stochastic geometry |
| title | A Stochastic Geometry Approach to EMF Exposure Modeling |
| title_full | A Stochastic Geometry Approach to EMF Exposure Modeling |
| title_fullStr | A Stochastic Geometry Approach to EMF Exposure Modeling |
| title_full_unstemmed | A Stochastic Geometry Approach to EMF Exposure Modeling |
| title_short | A Stochastic Geometry Approach to EMF Exposure Modeling |
| title_sort | stochastic geometry approach to emf exposure modeling |
| topic | Cellular networks exposure Poisson Point Process stochastic geometry |
| url | https://ieeexplore.ieee.org/document/9462948/ |
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