Air-to-Air Path Loss Prediction Based on Machine Learning Methods in Urban Environments
Joint Authors
He, Zunwen
Zhang, Yan
Wen, Jinxiao
Yang, Guanshu
Luo, Xinran
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-06-13
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
Recently, unmanned aerial vehicle (UAV) plays an important role in many applications because of its high flexibility and low cost.
To realize reliable UAV communications, a fundamental work is to investigate the propagation characteristics of the channels.
In this paper, we propose path loss models for the UAV air-to-air (AA) scenario based on machine learning.
A ray-tracing software is employed to generate samples for multiple routes in a typical urban environment, and different altitudes of Tx and Rx UAVs are taken into consideration.
Two machine-learning algorithms, Random Forest and KNN, are exploited to build prediction models on the basis of the training data.
The prediction performance of trained models is assessed on the test set according to the metrics including the mean absolute error (MAE) and root mean square error (RMSE).
Meanwhile, two empirical models are presented for comparison.
It is shown that the machine-learning-based models are able to provide high prediction accuracy and acceptable computational efficiency in the AA scenario.
Moreover, Random Forest outperforms other models and has the smallest prediction errors.
Further investigation is made to evaluate the impacts of five different parameters on the path loss.
It is demonstrated that the path visibility is crucial for the path loss.
American Psychological Association (APA)
Zhang, Yan& Wen, Jinxiao& Yang, Guanshu& He, Zunwen& Luo, Xinran. 2018. Air-to-Air Path Loss Prediction Based on Machine Learning Methods in Urban Environments. Wireless Communications and Mobile Computing،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1216303
Modern Language Association (MLA)
Zhang, Yan…[et al.]. Air-to-Air Path Loss Prediction Based on Machine Learning Methods in Urban Environments. Wireless Communications and Mobile Computing No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1216303
American Medical Association (AMA)
Zhang, Yan& Wen, Jinxiao& Yang, Guanshu& He, Zunwen& Luo, Xinran. Air-to-Air Path Loss Prediction Based on Machine Learning Methods in Urban Environments. Wireless Communications and Mobile Computing. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1216303
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1216303