A Statistical Estimation of 5G Massive MIMO’s Exposure using Stochastic Geometry

Hajj, Maarouf Al;Wang, Shanshan;Doncker, Philippe de;Oestges, Claude;Wiart, Joe
(2020) 2020 XXXIIIrd General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS) — Location: Rome, Italy (29.August.2020)

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Authors
  • Hajj, Maarouf Al
    Author
  • Wang, Shanshan
    Author
  • Doncker, Philippe de
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  • Oestges, Claudeorcid-logoUCLouvain
    Author
  • Wiart, Joe
    Author
Abstract
This paper aims to estimate the exposure in 5G massive MIMO networks using a stochastic geometric approach. The paper investigates the effect of beamforming, and the effect of multi-user massive MIMO on the exposure of a 5G network. The massive MIMO antenna pattern distribution is obtained by fitting the radiation pattern obtained by running a large amount of channel simulations on NYUSIM. The distribution is then implemented into an analytical framework based on stochastic geometry, so we can obtain a close form expression of the downlink exposure.
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Hajj, M. A., Wang, S., Doncker, P. d., Oestges, C., & Wiart, J. (2020). A Statistical Estimation of 5G Massive MIMO’s Exposure using Stochastic Geometry. Proceedings URSI GASS 2021. Published. 2020 XXXIIIrd General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS), Rome, Italy. https://doi.org/10.23919/ursigass49373.2020.9232290