Robust Trajectory and Resource Allocation Design for Secure UAV-Aided Communications

Abstract

This paper aims to enhance the physical layer security against potential internal eavesdroppings by exploiting the maneuverability of an unmanned aerial vehicle (UAV). We consider a scenario where two receivers with different security clearance levels require to be served by a legitimate transmitter with the aid of the UAV. We jointly design the trajectory and resource allocation to maximize the accumulated system confidential data rate. The design is formulated as a mixed-integer nonconvex optimization problem which takes into account the partial position information of a potential eavesdropper. To circumvent the problem non-convexity, a series of transformations and approximations are proposed which facilitates the design of a computationally efficient suboptimal solution. Simulation results are presented to provide important system design insights and demonstrate the advantages brought by the robust joint design for enhancing the physical layer security.

Robust Trajectory and Transmit Power Optimization for Secure UAV-Enabled Cognitive Radio Networks

“…It results in a significant security challenge for UAV-enabled CR networks. Besides conventional cryptography encryption methods enabling secure information transmission, physicallayer security technology has emerged as a promising alternative approach to guarantee the security of wireless communication systems by exploiting the physical layer characteristics of wireless channels [13]- [17]. In [18], the physical layer security of a UAV network was studied to jointly design the trajectory and transmission power of the UAV in order to maximize the minimum average secrecy rate of all users.…”

“…As a result, the trajectory design and power allocation based on the assumption of perfect location information may lead to a large performance loss for UAVenabled CR networks in practice. Recently, although the robust trajectory and transmit power designs have been considered in [16], [17], only the worst-case scenario has been studied. Specifically, in the worst-case scenario, the location errors are modeled by bounded sets.…”

“…To the best of our knowledge, this is the first work that studies the robust design of secure UAV-enabled CR networks under these two location error models. Although the bounded location error model has been studied in [16], [17], and the probabilistic location error model has been studied in [21], the proposed schemes in [16], [17] are only applicable to conventional wireless terrestrial communication networks and cannot work in UAV-enabled CR networks, and the physicallayer security issue in CR networks has not been considered in [21], and thus the security of the UAV-enabled network cannot be guaranteed. Different from existing works, the main contributions of this paper are summarized as follows.…”

“…Since UAVs generally operate above moderate altitude [8], the channels from the UAV to SU, PUs, and Eves are all dominated by LoS components [16], [17]. Thus, the distance between the UAV and the receivers can be used to determine the corresponding channels.…”

Resource Allocation for Secure Multi-UAV Communication Systems With Multi-Eavesdropper

“…Besides, several world-leading industrial companies, such as Facebook, Google, and Qualcomm, have made advancements on their journey to deliver high-speed internet from the air by UAVs [1]. As a result, the investigation of deploying UAVs for assisting wireless networks has recently received significant attention from the academia, such as mobile relays [7], [8], aerial mobile base stations [9], [10], and UAV-enabled information dissemination and data collection [1], [11].…”