Securing UAV Communications via Trajectory Optimization

Zhang, Guangchi; Wu, Qingqing; Cui, Miao; Zhang, Rui

doi:10.1109/glocom.2017.8254971

Cited by 127 publications

(138 citation statements)

References 21 publications

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“…For convenience, we define the set of all antenna elements as M ∆ = {1, · · · , M}. In order to guarantee flight safety, we assume that the UAV flies at constant altitude H 0 which is higher than the tallest obstacles in the service area [4]- [6]. Moreover, we define v u [n]…”

Section: A Multiuser Uav Communication Systemmentioning

confidence: 99%

See 1 more Smart Citation

Multiuser MISO UAV Communications in Uncertain Environments With No-Fly Zones: Robust Trajectory and Resource Allocation Design

Sun

et al. 2020

IEEE Trans. Commun.

172

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In this paper, we investigate robust resource allocation algorithm design for multiuser downlink multiple-input single-output (MISO) unmanned aerial vehicle (UAV) communication systems, where we account for the various uncertainties that are unavoidable in such systems and, if left unattended, may severely degrade system performance.We jointly optimize the two-dimensional (2-D) trajectory and the transmit beamforming vector of the UAV for minimization of the total power consumption. The algorithm design is formulated as a non-convex optimization problem taking into account the imperfect knowledge of the angle of departure (AoD) caused by UAV jittering, user location uncertainty, wind speed uncertainty, and polygonal no-fly zones (NFZs). Despite the non-convexity of the optimization problem, we solve it optimally by employing monotonic optimization theory and semidefinite programming relaxation which yields the optimal 2-D trajectory and beamforming policy. Since the developed optimal resource allocation algorithm entails a high computational complexity, we also propose a suboptimal iterative low-complexity scheme based on successive convex approximation to strike a balance between optimality and computational complexity. Our simulation results reveal not only the significant power savings enabled by the proposed algorithms compared to two baseline schemes, but also confirm their robustness with respect to UAV jittering, wind speed uncertainty, and user location uncertainty. Moreover, our results unveil that the joint presence of wind speed uncertainty and NFZs has a considerable impact on the UAV trajectory. Nevertheless, by counteracting the wind speed uncertainty with the proposed robust design, we can simultaneously minimize the total UAV power consumption and ensure a secure trajectory that does not trespass any NFZ. ). This paper was presented in part at IEEE Globecom 2018 [1]. 2 be employed as aerial base stations to offer temporary communication links in a timely and cost-effective manner. Moreover, due to their high mobility and maneuverability, UAVs can adapt their trajectories based on the actual environment and terrain which improves system performance [3]. As a result, UAV-assisted communication systems have drawn significant attention from both academia and industry. For instance, the authors of [4] studied suboptimal UAV trajectory design for maximization of the energy-efficiency of UAV communication systems. The authors of [5] proposed a suboptimal joint trajectory, power allocation, and user scheduling algorithm for maximization of the minimum user throughput in multi-UAV systems.Secure UAV communications was investigated in [6] where the trajectory of a UAV and its transmit power were jointly optimized to maximize the system secrecy rate. The authors of [7] proposed solar-powered UAV communication systems and studied the jointly optimal resource allocation and UAV trajectory design for maximization of the system sum throughput. In fact, the throughput of UAV communication systems can be further i...

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Section: A Multiuser Uav Communication Systemmentioning

confidence: 99%

“…Secure UAV communications was investigated in [6] where the trajectory of a UAV and its transmit power were jointly optimized to maximize the system secrecy rate. The authors of [7] proposed solar-powered UAV communication systems and studied the jointly optimal resource allocation and UAV trajectory design for maximization of the system sum throughput.…”

mentioning

confidence: 99%

Multiuser MISO UAV Communications in Uncertain Environments With No-Fly Zones: Robust Trajectory and Resource Allocation Design

Sun

et al. 2020

IEEE Trans. Commun.

172

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“…March 17, 2020 DRAFT Next, we handle the binary user scheduling constraint C2 in (21). In particular, we follow a similar approach as in [1], [41] and relax the binary subcarrier variable s m,k U ,i [n] as a real value between 0 and 1, i.e.,…”

Section: A Subproblem 1: Communication Resource Allocation Optimizationmentioning

confidence: 99%

“…s m,k U ,i [n] = 1 and p m,k U ,i [n] > 0, under the condition H m,k U ,i [n] ≤ H m,k E ,i [n], we have ñR m,k U ,i [n] −R m,k U ,k E ,i [n]ô ≤ 0, which leads to a smaller objective value in(21). Besides, the solution set becomes smaller as some power is wasted without improving the objective value.…”

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confidence: 99%

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

Wei

Yang

et al. 2020

IEEE Trans. Commun.

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In this paper, we study the resource allocation and trajectory design for secure unmanned aerial vehicle (UAV)-enabled communication systems, where multiple multi-purpose UAV base stations are dispatched to provide secure communications to multiple legitimate ground users (GUs) in the existence of multiple eavesdroppers (Eves). Specifically, by leveraging orthogonal frequency division multiple access (OFDMA), active UAV base stations can communicate to their desired ground users via the assigned subcarriers while idle UAV base stations can serve as jammer simultaneously for communication security provisioning. To achieve fairness in secure communication, we maximize the average minimum secrecy rate per user by jointly optimizing the communication/jamming subcarrier allocation policy and the trajectory of UAVs, while taking into account the constraints on the minimum safety distance among multiple UAVs, the maximum cruising speed, the initial/final locations, and the existence of cylindrical no-fly zones (NFZs). The design is formulated as a mixed integer non-convex optimization problem which is generally intractable. Subsequently, a computationally-efficient iterative algorithm is proposed to obtain a suboptimal solution. Simulation results illustrate that the performance of the proposed iterative algorithm can significantly improve the average minimum secrecy rate compared to various baseline schemes. R. Li and J. An are with the secure UAV communication systems with a single-UAV was studied in [8], [14]-[16] with different system settings. However, due to the stringent requirements on UAV's size, weight, and power (SWAP), the performance achieved by deploying a single-UAV is still limited [6]. To achieve a higher efficiency in secure communications, multi-UAV cooperation was adopted in [17]-[20]. In particular, a jammer UAV can fly close to a potential eavesdropper based on demand by leveraging its mobility and opportunistically transmits artificial noise signal deliberately to combat the eavesdropping channels [17]. To improve the system security performance, [18] and [19] presented a cooperative jamming approach to safeguard the UAV's communication by exploiting artificial jamming transmission from other friend UAVs in the existence of a single-eavesdropper. With the consideration of fairness in two-UAV secure communications, [20] investigated the joint power allocation and trajectory design for the maximization of the minimum secrecy rate per user when one UAV is dispatched to convey confidential messages to a ground user where another cooperative UAV transmits a jamming signal. However, in [17]-[20], the role of the UAV is fixed where a communication/jamming UAV can only provide either communication/jamming signal during the whole time horizon.In contrast, a multi-purpose UAV, which can dynamically serve as a communication UAV or a jamming UAV, provides a high flexibility in trajectory design for secure UAV communications. March 17, 2020 DRAFT 3 For instance, when a communication UAV flies closer to an eave...

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“…For example, UAV-aided jamming scheme was proposed to handle the security issues in [4]. Besides, joint trajectory and resource allocation design was investigated in [5]- [7] for improving the system secrecy rate with UAV-mounted base stations and UAVaided relaying protocols, respectively. However, the previous works are all based on an assumption that accurate position information of eavesdroppers is available at UAVs which is over optimistic.…”

Section: Introductionmentioning

confidence: 99%

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

Sun

Shen

et al. 2019

2019 IEEE International Conference on Communications Workshops (ICC Workshops)

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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.

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Securing UAV Communications via Trajectory Optimization

Cited by 127 publications

References 21 publications

Multiuser MISO UAV Communications in Uncertain Environments With No-Fly Zones: Robust Trajectory and Resource Allocation Design

Multiuser MISO UAV Communications in Uncertain Environments With No-Fly Zones: Robust Trajectory and Resource Allocation Design

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

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

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