UAV Communication Recovery under Meteorological Conditions
Our study proposes a UAV communications recovery strategy under meteorological conditions based on a ray tracing simulation of excessive path loss in four distinct three-dimensional (3D) urban environments. We start by reviewing the air-to-ground propagation loss model under meteorological condition...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/7/7/423 |
| _version_ | 1797589585609359360 |
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| author | Mengan Song Yiming Huo Zhonghua Liang Xiaodai Dong Tao Lu |
| author_facet | Mengan Song Yiming Huo Zhonghua Liang Xiaodai Dong Tao Lu |
| author_sort | Mengan Song |
| collection | DOAJ |
| description | Our study proposes a UAV communications recovery strategy under meteorological conditions based on a ray tracing simulation of excessive path loss in four distinct three-dimensional (3D) urban environments. We start by reviewing the air-to-ground propagation loss model under meteorological conditions, as well as the specific attenuation of rain, fog, and snow, and we propose a new expression for line-of-sight (LoS) probability. Using the two frequency bands of 28 GHz and 71 GHz, we investigate the impact of specific attenuation caused by different weather conditions and analyze the relationship between the radius of the UAV coverage area and the elevation angle. Furthermore, we investigate the effects of the rainfall rate, liquid water density, and snowfall rate on the maximum coverage area and optimal height of the UAV. Eventually, we propose a strategy that involves compensating for the maximum path loss and adjusting the UAV’s position to recover the coverage of the UAV to ground users. Our results show that rain has the greatest impact on the UAV’s coverage area and optimum height among the three types of weather conditions. For various weather conditions, relative to Region 1, the percentage reduction in the maximum coverage radius of Region 2 to Region 4 increases gradually, and the extent of each increase is approximately 10%. Moreover, after adding the compensated path loss, the coverage radius of the UAV in the four regions is restored to a value slightly larger than that before the rain. In addition, rain caused the greatest reduction in UAV coverage for suburban environments and the lowest for high-rise urban environments. |
| first_indexed | 2024-03-11T01:08:32Z |
| format | Article |
| id | doaj.art-2f36c7022b6242178a6efe6e30a68ff3 |
| institution | Directory Open Access Journal |
| issn | 2504-446X |
| language | English |
| last_indexed | 2024-03-11T01:08:32Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj.art-2f36c7022b6242178a6efe6e30a68ff32023-11-18T19:00:51ZengMDPI AGDrones2504-446X2023-06-017742310.3390/drones7070423UAV Communication Recovery under Meteorological ConditionsMengan Song0Yiming Huo1Zhonghua Liang2Xiaodai Dong3Tao Lu4School of Information Engineering, Chang’an University, Xi’an 710064, ChinaDepartment of Electrical and Computer Engineering, University of Victoria, Victoria, BC V8P 5C2, CanadaSchool of Information Engineering, Chang’an University, Xi’an 710064, ChinaDepartment of Electrical and Computer Engineering, University of Victoria, Victoria, BC V8P 5C2, CanadaDepartment of Electrical and Computer Engineering, University of Victoria, Victoria, BC V8P 5C2, CanadaOur study proposes a UAV communications recovery strategy under meteorological conditions based on a ray tracing simulation of excessive path loss in four distinct three-dimensional (3D) urban environments. We start by reviewing the air-to-ground propagation loss model under meteorological conditions, as well as the specific attenuation of rain, fog, and snow, and we propose a new expression for line-of-sight (LoS) probability. Using the two frequency bands of 28 GHz and 71 GHz, we investigate the impact of specific attenuation caused by different weather conditions and analyze the relationship between the radius of the UAV coverage area and the elevation angle. Furthermore, we investigate the effects of the rainfall rate, liquid water density, and snowfall rate on the maximum coverage area and optimal height of the UAV. Eventually, we propose a strategy that involves compensating for the maximum path loss and adjusting the UAV’s position to recover the coverage of the UAV to ground users. Our results show that rain has the greatest impact on the UAV’s coverage area and optimum height among the three types of weather conditions. For various weather conditions, relative to Region 1, the percentage reduction in the maximum coverage radius of Region 2 to Region 4 increases gradually, and the extent of each increase is approximately 10%. Moreover, after adding the compensated path loss, the coverage radius of the UAV in the four regions is restored to a value slightly larger than that before the rain. In addition, rain caused the greatest reduction in UAV coverage for suburban environments and the lowest for high-rise urban environments.https://www.mdpi.com/2504-446X/7/7/423unmanned aerial vehicle (UAV)air-to-ground (A2G)meteorological conditionschannel modelsray tracing (RT)excessive path loss |
| spellingShingle | Mengan Song Yiming Huo Zhonghua Liang Xiaodai Dong Tao Lu UAV Communication Recovery under Meteorological Conditions Drones unmanned aerial vehicle (UAV) air-to-ground (A2G) meteorological conditions channel models ray tracing (RT) excessive path loss |
| title | UAV Communication Recovery under Meteorological Conditions |
| title_full | UAV Communication Recovery under Meteorological Conditions |
| title_fullStr | UAV Communication Recovery under Meteorological Conditions |
| title_full_unstemmed | UAV Communication Recovery under Meteorological Conditions |
| title_short | UAV Communication Recovery under Meteorological Conditions |
| title_sort | uav communication recovery under meteorological conditions |
| topic | unmanned aerial vehicle (UAV) air-to-ground (A2G) meteorological conditions channel models ray tracing (RT) excessive path loss |
| url | https://www.mdpi.com/2504-446X/7/7/423 |
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