On the Impact of Dynamic Beamforming on EMF Exposure and Network Coverage: A Stochastic Geometry Perspective
Quentin Gontier, Charles Wiame, Joe Wiart, Fran\c{c}ois Horlin,, Christo Tsigros, Claude Oestges, Philippe De Doncker

TL;DR
This paper develops a stochastic geometry framework for dynamic beamforming in cellular networks, introducing a multi-cosine antenna pattern and the SCAIU metric to analyze EMF exposure and coverage, revealing key antenna element thresholds for performance and safety.
Contribution
It presents a novel stochastic geometry model with a multi-cosine antenna pattern and introduces the SCAIU metric to balance coverage and EMF exposure in dynamic beamforming networks.
Findings
Multi-cosine antenna pattern reduces modeling error to less than 2%.
Active user SINR remains above 10 dB with over 256 antenna elements.
Idle user EMFE becomes negligible beyond 60 meters with 64 antennas.
Abstract
This paper introduces a new mathematical framework for dynamic beamforming-based cellular networks, grounded in stochastic geometry. The framework is used to study the electromagnetic field exposure (EMFE) of active and idle users as a function of the distance between them. A novel multi-cosine antenna pattern is introduced, offering more accurate modeling by incorporating both main and side lobes. Results show that the cumulative distribution functions of EMFE and coverage obtained with the multi-cosine pattern align closely with theoretical models, reducing error to less than 2\%, compared to a minimum of 8\% for other models. The marginal distribution of EMFE for each user type is mathematically derived. A unique contribution is the introduction of the SCAIU (\underline{S}patial \underline{C}DF for \underline{A}ctive and \underline{I}dle \underline{U}sers), a metric that ensures…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization · Millimeter-Wave Propagation and Modeling
