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Article

A Statistical Estimation of 5G Massive MIMO Networks’ Exposure Using Stochastic Geometry in mmWave Bands

1
Chaire C2M, LTCI, Télécom Paris, 19 Place Marguerite Perey, 91120 Palaiseau, France
2
Institute XLIM, University of Poitiers, 15 Rue de l’Hôtel Dieu, TSA 71117, 86000 Poitiers, France
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(23), 8753; https://doi.org/10.3390/app10238753
Received: 30 October 2020 / Revised: 25 November 2020 / Accepted: 2 December 2020 / Published: 7 December 2020
(This article belongs to the Special Issue Human Exposure in 5G and 6G Scenarios)
This paper aims to derive an analytical modelling of the downlink exposure in 5G massive Multiple Input Multiple Output (MIMO) antenna networks using stochastic geometry. The Poisson point process (PPP) is assumed for base station (BS) distribution. The power received at the transmitter is modeled as a shot-noise process with a modified power law. The distributions of 5G massive MIMO antenna gain and channel gain were obtained by fitting simulation results from the NYUSIM channel simulator. The fitted distributions, e.g., exponential and gamma distribution for antenna and channel gain respectively, were then implemented into an analytical framework. In this paper, we obtained the closed-form expression of the moment-generating function (MGF) for the total exposure in the network. The framework is then validated by numerical simulations. The sensitivity analysis is carried out to investigate the impact of key parameters, e.g., BS density, path loss exponent, and transmission probability. We then proved and quantified the significant impact the transmission probability on global exposure, which indicates the importance of considering the network usage in 5G exposure estimations. View Full-Text
Keywords: stochastic geometry; massive MIMO; electromagnetic field exposure; 5G stochastic geometry; massive MIMO; electromagnetic field exposure; 5G
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MDPI and ACS Style

Al Hajj, M.; Wang, S.; Thanh Tu, L.; Azzi, S.; Wiart, J. A Statistical Estimation of 5G Massive MIMO Networks’ Exposure Using Stochastic Geometry in mmWave Bands. Appl. Sci. 2020, 10, 8753. https://doi.org/10.3390/app10238753

AMA Style

Al Hajj M, Wang S, Thanh Tu L, Azzi S, Wiart J. A Statistical Estimation of 5G Massive MIMO Networks’ Exposure Using Stochastic Geometry in mmWave Bands. Applied Sciences. 2020; 10(23):8753. https://doi.org/10.3390/app10238753

Chicago/Turabian Style

Al Hajj, Maarouf, Shanshan Wang, Lam Thanh Tu, Soumaya Azzi, and Joe Wiart. 2020. "A Statistical Estimation of 5G Massive MIMO Networks’ Exposure Using Stochastic Geometry in mmWave Bands" Applied Sciences 10, no. 23: 8753. https://doi.org/10.3390/app10238753

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