Secrecy Outage Performance of Ground-to-Air Communications with Multiple Aerial Eavesdroppers and Its Deep Learning Evaluation
Author | Bao T. |
Author | Zhu J. |
Author | Yang H.-C. |
Author | Hasna , Mazen |
Available date | 2022-04-26T11:06:45Z |
Publication Date | 2020 |
Publication Name | IEEE Wireless Communications Letters |
Resource | Scopus |
Identifier | http://dx.doi.org/10.1109/LWC.2020.2990337 |
Abstract | In this letter, we study the secure information transmission from a ground base station (GBS) to a legitimate unmanned aerial vehicle (UAV) user, in the presence of multiple UAV eavesdroppers. To enhance the secrecy performance, the GBS applies beamforming transmission while enforcing a protection zone around it. Utilizing the general shadowed fading distribution to model the ground-to-air channel, we derive an exact expression of the secrecy outage probability (SOP). To further facilitate performance evaluation, we adopt a data-driven approach and develop a deep learning model that can predict the SOP performance with high accuracy and short computation time. Through selected numerical results, we examine the effect of different system parameters on the SOP performance. |
Sponsor | Qatar University |
Language | en |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Subject | Antennas Probability distributions Unmanned aerial vehicles (UAV) Vehicle transmissions Data-driven approach Fading distribution Ground base stations Ground-to-air communication Information transmission Learning evaluations Numerical results Secrecy outage probabilities Deep learning |
Type | Article |
Pagination | 1351-1355 |
Issue Number | 9 |
Volume Number | 9 |
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Electrical Engineering [2611 items ]