Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/98856
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Title: Energy-efficient joint UAV secure communication and 3D trajectory optimization assisted by reconfigurable intelligent surfaces in the presence of eavesdroppers
Authors: Huang, H 
Mohsen, E
Savkin, AV
Wei, N
Issue Date: Jan-2024
Source: Defence technology, Jan. 2024, v. 31, p. 537-543
Abstract: We consider a scenario where an unmanned aerial vehicle (UAV), a typical unmanned aerial system (UAS), transmits confidential data to a moving ground target in the presence of multiple eavesdroppers. Multiple friendly reconfigurable intelligent surfaces (RISs) help to secure the UAV-target communication and improve the energy efficiency of the UAV. We formulate an optimization problem to minimize the energy consumption of the UAV, subject to the mobility constraint of the UAV and that the achievable secrecy rate at the target is over a given threshold. We present an online planning method following the framework of model predictive control (MPC) to jointly optimize the motion of the UAV and the configurations of the RISs. The effectiveness of the proposed method is validated via computer simulations.
Keywords: Autonomous navigation and placement
Communication security
Eaves-dropping
Model predictive control
Path planning
Reconfigurable intelligent surfaces (RIS)
Unmanned aerial systems (UASs)
Unmanned aerial vehicle (UAV)
Publisher: Ke Ai Publishing Communications Ltd.
Journal: Defence technology 
ISSN: 2096-3459
EISSN: 2214-9147
DOI: 10.1016/j.dt.2022.12.010
Rights: © 2022 China Ordnance Society. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
The following publication Hailong, H., Eskandari, M., Savkin, A. V., & Ni, W. (2024). Energy-efficient joint UAV secure communication and 3D trajectory optimization assisted by reconfigurable intelligent surfaces in the presence of eavesdroppers. Defence Technology, 31, 537-543 is available at https://doi.org/10.1016/j.dt.2022.12.010.
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