Near-Ground Path Loss Measurements and Modeling for Wireless Sensor Networks at 2.4 GHz
Near-ground channel characterization is an important issue in most military applications of wireless sensor networks. However, the channel at the ground level lacks characterization. In this paper, we present a path loss model for three near-ground scenarios. The path loss values for each scenario w...
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2012-08-01
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Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1155/2012/969712 |
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doaj-e3903bd8004143239e806400edf7aa012020-11-25T03:43:39ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772012-08-01810.1155/2012/969712Near-Ground Path Loss Measurements and Modeling for Wireless Sensor Networks at 2.4 GHzDaihua Wang0Linli Song1Xiangshan Kong2Zhijie Zhang3 National Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan 030051, China Key Laboratory of Instrumentation Science and Dynamic Measurement of The Ministry of Education, North University of China, Taiyuan 030051, China North Automatic Control Technology Institute, CNGC, Taiyuan 030006, China National Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan 030051, ChinaNear-ground channel characterization is an important issue in most military applications of wireless sensor networks. However, the channel at the ground level lacks characterization. In this paper, we present a path loss model for three near-ground scenarios. The path loss values for each scenario were captured through extensive measurements, and then a least-square linear regression was performed. This indicates that the log-distance-based model is still suitable for path loss modeling in near-ground scenarios, and the prediction accuracy of the two-slope model is superior to that of the one-slope model. The validity of the proposed model was further verified by comparisons between the predicted and measured far-field path losses. Finally, compared to the generic models, the proposed model is more effective for the path loss prediction in near-ground scenarios.https://doi.org/10.1155/2012/969712 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Daihua Wang Linli Song Xiangshan Kong Zhijie Zhang |
spellingShingle |
Daihua Wang Linli Song Xiangshan Kong Zhijie Zhang Near-Ground Path Loss Measurements and Modeling for Wireless Sensor Networks at 2.4 GHz International Journal of Distributed Sensor Networks |
author_facet |
Daihua Wang Linli Song Xiangshan Kong Zhijie Zhang |
author_sort |
Daihua Wang |
title |
Near-Ground Path Loss Measurements and Modeling for Wireless Sensor Networks at 2.4 GHz |
title_short |
Near-Ground Path Loss Measurements and Modeling for Wireless Sensor Networks at 2.4 GHz |
title_full |
Near-Ground Path Loss Measurements and Modeling for Wireless Sensor Networks at 2.4 GHz |
title_fullStr |
Near-Ground Path Loss Measurements and Modeling for Wireless Sensor Networks at 2.4 GHz |
title_full_unstemmed |
Near-Ground Path Loss Measurements and Modeling for Wireless Sensor Networks at 2.4 GHz |
title_sort |
near-ground path loss measurements and modeling for wireless sensor networks at 2.4 ghz |
publisher |
SAGE Publishing |
series |
International Journal of Distributed Sensor Networks |
issn |
1550-1477 |
publishDate |
2012-08-01 |
description |
Near-ground channel characterization is an important issue in most military applications of wireless sensor networks. However, the channel at the ground level lacks characterization. In this paper, we present a path loss model for three near-ground scenarios. The path loss values for each scenario were captured through extensive measurements, and then a least-square linear regression was performed. This indicates that the log-distance-based model is still suitable for path loss modeling in near-ground scenarios, and the prediction accuracy of the two-slope model is superior to that of the one-slope model. The validity of the proposed model was further verified by comparisons between the predicted and measured far-field path losses. Finally, compared to the generic models, the proposed model is more effective for the path loss prediction in near-ground scenarios. |
url |
https://doi.org/10.1155/2012/969712 |
work_keys_str_mv |
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1724518465637711872 |