A Combined Stochastic and Physical Framework for Modeling Indoor 5G Millimeter Wave Propagation

Indoor coverage is a major challenge for 5G millimeter waves (mmWaves). In this paper, we address this problem through a novel theoretical framework that combines stochastic indoor environment modeling with advanced physical propagation simulation. This approach is particularly adapted to investigat...

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Vydané v:IEEE transactions on antennas and propagation Ročník 70; číslo 6; s. 1
Hlavní autori: Nassif, Georges, Gloaguen, Catherine, Martins, Philippe
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.06.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers
Predmet:
5G mobile communication
Algorithms
electromagnetic diffusion
Electromagnetic radiation
Engineering Sciences
Environment models
Geometry
Indoor environment
Indoor environments
link budget
Material properties
millimeter wave propagation
Millimeter waves
Optimization
physical modeling
Propagation
Radio transmission
Rough surfaces
Simulation
simulation optimization
stochastic geometry
Stochastic processes
Surface roughness
Surface waves
Wave propagation
ISSN:0018-926X, 1558-2221
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Shrnutí:Indoor coverage is a major challenge for 5G millimeter waves (mmWaves). In this paper, we address this problem through a novel theoretical framework that combines stochastic indoor environment modeling with advanced physical propagation simulation. This approach is particularly adapted to investigate indoor-to-indoor 5G mmWave propagation. Its system implementation, so-called iGeoStat, generates parameterized typical environments that account for the indoor spatial variations, then simulates radio propagation based on the physical interaction between electromagnetic waves and material properties. This framework is not dedicated to a particular environment, material, frequency, or use case, and aims to statistically understand the influence of indoor environment parameters on mmWave propagation properties, especially coverage and path loss. Its implementation raises numerous computational challenges that we solve by formulating an adapted link budget and designing new memory optimization algorithms. The first simulation results for two major 5G applications are validated with measurement data and show the efficiency of iGeoStat to simulate multiple diffusion in realistic environments, within a reasonable amount of time and memory resources. Generated output maps confirm that diffusion has a critical impact on indoor mmWave propagation and that proper physical modeling is of the utmost importance to generate relevant propagation models.
Bibliografia:ObjectType-Article-1
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ISSN:0018-926X
1558-2221
DOI:10.1109/TAP.2022.3161286