A 3D Non-Stationary Wideband GBSM for Low-Altitude UAV-to-Ground V2V MIMO Channels
Due to the high-mobility of unmanned aerial vehicles (UAVs), actual UAV channel measurements show that low-altitude air-to-ground (A2G) channels in UAV communications illustrate non-stationary properties. This fact motivates us to develop a non-stationary channel model for UAV-to-ground links. In th...
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2019-01-01
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author | Hengtai Chang Ji Bian Cheng-Xiang Wang Zhiquan Bai Wenqi Zhou el-Hadi M. Aggoune |
author_facet | Hengtai Chang Ji Bian Cheng-Xiang Wang Zhiquan Bai Wenqi Zhou el-Hadi M. Aggoune |
author_sort | Hengtai Chang |
collection | DOAJ |
description | Due to the high-mobility of unmanned aerial vehicles (UAVs), actual UAV channel measurements show that low-altitude air-to-ground (A2G) channels in UAV communications illustrate non-stationary properties. This fact motivates us to develop a non-stationary channel model for UAV-to-ground links. In this paper, we propose a three-dimensional (3D) wideband non-stationary A2G vehicle-to-vehicle (V2V) geometry-based stochastic channel model (GBSM). In the proposed model, both UAVs and ground terminals can be moving, which makes the model more general. In order to mimic the non-stationary channel characteristics, parameters like the number of clusters, power, time delays, angels of departure (AoDs), and angles of arrival (AoAs) are all time-variant. The proposed model combining a line-of-sight (LoS) component, a ground reflection component, a cylinder model, and multiple confocal truncated ellipsoid models has the ability to investigate the impact of UAV heights and transceivers' movements on channel characteristics in diverse environments. Statistical properties like temporal autocorrelation function (ACF), spatial cross-correlation function (CCF), Doppler power spectral density (PSD), and stationary interval of A2G channels are derived and analyzed in detail. In addition, derived root mean square delay spread (RMS-DS), temporal ACF and spatial CCF are validated against channel measurement results. Furthermore, by adjusting channel parameters, the proposed GBSM is sufficiently generic and adaptable to model various UAV-to-ground communication scenarios. |
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issn | 2169-3536 |
language | English |
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publishDate | 2019-01-01 |
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spelling | doaj.art-e2e1696d3f61471d904c78cc971299fc2022-12-21T18:13:22ZengIEEEIEEE Access2169-35362019-01-017707197073210.1109/ACCESS.2019.29197908725553A 3D Non-Stationary Wideband GBSM for Low-Altitude UAV-to-Ground V2V MIMO ChannelsHengtai Chang0Ji Bian1Cheng-Xiang Wang2https://orcid.org/0000-0002-9729-9592Zhiquan Bai3https://orcid.org/0000-0002-8716-3691Wenqi Zhou4el-Hadi M. Aggoune5Shandong Provincial Key Lab of Wireless Communication Technologies, School of Information Science and Engineering, Shandong University, Qingdao, ChinaShandong Provincial Key Lab of Wireless Communication Technologies, School of Information Science and Engineering, Shandong University, Qingdao, ChinaNational Mobile Communications Research Laboratory, School of Information Science and Engineering, Southeast University, Nanjing, ChinaShandong Provincial Key Lab of Wireless Communication Technologies, School of Information Science and Engineering, Shandong University, Qingdao, ChinaShandong Huahan Electronics Co., Ltd., Jinan, ChinaSensor Networks and Cellular Systems Research Center, University of Tabuk, Tabuk, Saudi ArabiaDue to the high-mobility of unmanned aerial vehicles (UAVs), actual UAV channel measurements show that low-altitude air-to-ground (A2G) channels in UAV communications illustrate non-stationary properties. This fact motivates us to develop a non-stationary channel model for UAV-to-ground links. In this paper, we propose a three-dimensional (3D) wideband non-stationary A2G vehicle-to-vehicle (V2V) geometry-based stochastic channel model (GBSM). In the proposed model, both UAVs and ground terminals can be moving, which makes the model more general. In order to mimic the non-stationary channel characteristics, parameters like the number of clusters, power, time delays, angels of departure (AoDs), and angles of arrival (AoAs) are all time-variant. The proposed model combining a line-of-sight (LoS) component, a ground reflection component, a cylinder model, and multiple confocal truncated ellipsoid models has the ability to investigate the impact of UAV heights and transceivers' movements on channel characteristics in diverse environments. Statistical properties like temporal autocorrelation function (ACF), spatial cross-correlation function (CCF), Doppler power spectral density (PSD), and stationary interval of A2G channels are derived and analyzed in detail. In addition, derived root mean square delay spread (RMS-DS), temporal ACF and spatial CCF are validated against channel measurement results. Furthermore, by adjusting channel parameters, the proposed GBSM is sufficiently generic and adaptable to model various UAV-to-ground communication scenarios.https://ieeexplore.ieee.org/document/8725553/Unmanned aerial vehiclesUAV-to-ground V2V MIMO channel modelsnon-stationary channel modelsGBSMstatistical properties |
spellingShingle | Hengtai Chang Ji Bian Cheng-Xiang Wang Zhiquan Bai Wenqi Zhou el-Hadi M. Aggoune A 3D Non-Stationary Wideband GBSM for Low-Altitude UAV-to-Ground V2V MIMO Channels IEEE Access Unmanned aerial vehicles UAV-to-ground V2V MIMO channel models non-stationary channel models GBSM statistical properties |
title | A 3D Non-Stationary Wideband GBSM for Low-Altitude UAV-to-Ground V2V MIMO Channels |
title_full | A 3D Non-Stationary Wideband GBSM for Low-Altitude UAV-to-Ground V2V MIMO Channels |
title_fullStr | A 3D Non-Stationary Wideband GBSM for Low-Altitude UAV-to-Ground V2V MIMO Channels |
title_full_unstemmed | A 3D Non-Stationary Wideband GBSM for Low-Altitude UAV-to-Ground V2V MIMO Channels |
title_short | A 3D Non-Stationary Wideband GBSM for Low-Altitude UAV-to-Ground V2V MIMO Channels |
title_sort | 3d non stationary wideband gbsm for low altitude uav to ground v2v mimo channels |
topic | Unmanned aerial vehicles UAV-to-ground V2V MIMO channel models non-stationary channel models GBSM statistical properties |
url | https://ieeexplore.ieee.org/document/8725553/ |
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