A Novel Nonstationary 6G UAV-to-Ground Wireless Channel Model With 3-D Arbitrary Trajectory Changes

In order to provide reliable and efficient connections between unmanned aerial vehicles (UAVs) and ground stations (GSs), realistic UAV-to-ground channel models are indispensable. In this article, we propose a novel 3-D nonstationary geometry-based stochastic model (GBSM) for UAV-to-ground multiple-...

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Bibliographic Details
Published in:IEEE internet of things journal Vol. 8; no. 12; pp. 9865 - 9877
Main Authors: Chang, Hengtai, Wang, Cheng-Xiang, Liu, Yu, Huang, Jie, Sun, Jian, Zhang, Wensheng, Gao, Xiqi
Format: Journal Article
Language:English
Published: Piscataway IEEE 15.06.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
3-D nonstationary wireless channel models
6G mobile communication
arbitrary UAV trajectory
Channel models
Design optimization
Fading channels
Frequencies
geometry-based stochastic model (GBSM)
Ground stations
Internet of Things
Millimeter waves
MIMO communication
Model accuracy
Performance evaluation
Stochastic models
Stochastic processes
Three dimensional models
Three dimensional motion
Three-dimensional displays
Time correlation functions
Trajectory
Unmanned aerial vehicles
unmanned aerial vehicles (UAVs)
Wireless networks
ISSN:2327-4662, 2327-4662
Online Access:Get full text
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Summary:In order to provide reliable and efficient connections between unmanned aerial vehicles (UAVs) and ground stations (GSs), realistic UAV-to-ground channel models are indispensable. In this article, we propose a novel 3-D nonstationary geometry-based stochastic model (GBSM) for UAV-to-ground multiple-input-multiple-output (MIMO) channels. Distinctive UAV-to-ground channel characteristics, such as time-domain nonstationarity, distinctions between different altitudes, spatial consistency, and 3-D arbitrary UAV movement trajectories, are taken into account. By adjusting parameter settings, the proposed channel model framework is sufficiently general to support multiple frequency bands and multiple scenarios, including millimeter wave (mmWave) and massive MIMO configurations. Statistical properties, including power delay profile (PDP), stationary interval, space-time correlation function (STCF), and root-mean-square (RMS) delay spread are derived and analyzed for different frequencies and scenarios. The accuracy of the proposed model is validated by comparing its statistical properties with corresponding available channel measurements. The proposed channel model will provide a fundamental support for the design, performance evaluation, and optimization of future UAV integrated sixth-generation (6G) wireless networks.
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ISSN:2327-4662
2327-4662
DOI:10.1109/JIOT.2020.3018479