Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/164289
Title: IRS-assisted secure UAV transmission via joint trajectory and beamforming design
Authors: Pang, Xiaowei
Zhao, Nan
Tang, Jie
Wu, Celimuge
Niyato, Dusit
Wong, Kai-Kit
Keywords: Engineering::Computer science and engineering
Issue Date: 2021
Source: Pang, X., Zhao, N., Tang, J., Wu, C., Niyato, D. & Wong, K. (2021). IRS-assisted secure UAV transmission via joint trajectory and beamforming design. IEEE Transactions On Communications, 70(2), 1140-1152. https://dx.doi.org/10.1109/TCOMM.2021.3136563
Journal: IEEE Transactions on Communications
Abstract: Despite the wide utilization of unmanned aerial vehicles (UAVs), UAV communications are susceptible to eavesdropping due to air-ground line-of-sight channels. Intelligent reflecting surface (IRS) is capable of reconfiguring the propagation environment, and thus is an attractive solution for integrating with UAV to facilitate the security in wireless networks. In this paper, we investigate the secure transmission design for an IRS-assisted UAV network in the presence of an eavesdropper. With the aim at maximizing the average secrecy rate, the trajectory of UAV, the transmit beamforming, and the phase shift of IRS are jointly optimized. To address this sophisticated problem, we decompose it into three sub-problems and resort to an iterative algorithm to solve them alternately. First, we derive the closed-form solution to the active beamforming. Then, with the optimal transmit beamforming, the passive beamforming optimization problem of fractional programming is transformed into corresponding parametric sub-problems. Moreover, the successive convex approximation is applied to deal with the non-convex UAV trajectory optimization problem by reformulating a convex problem which serves as a lower bound for the original one. Simulation results validate the effectiveness of the proposed scheme and the performance improvement achieved by the joint trajectory and beamforming design.
URI: https://hdl.handle.net/10356/164289
ISSN: 0090-6778
DOI: 10.1109/TCOMM.2021.3136563
Rights: © 2021 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
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