Unmanned aerial vehicle (UAV) can enable cellular mobile communications in unexpected or temporary scenarios, but there are information security problems raised in such applications. Physical layer security is now emerging as a promising alternative technology to realize secrecy in wireless communications. In the UAV-enabled communication systems, the fully controllable mobility of UAV provides new design degrees of freedom for enhancing physical layer security. This paper investigates an UAV-enabled cellular communication system where an ultralow-altitude UAV is equipped with a base station to serve a ground user in the presence of an eavesdropper. The probability of non-zero secrecy capacity is maximized subject to the airspace and obstacle constraints by adaptively optimizing the UAV’s three-dimensional positions. The optimization problem is simplified by equivalent transformation and then solved by semidefinite relaxation (SDR). Two approaches termed as eigenvector approximation and random sampling are addressed to extract an approximation solution for the primal problem from the solution obtained by the SDR. Simulation results show that there is a slight difference between the probability of non-zero secrecy capacity achieved by the two solution approximation approaches.

Low-altitude cellular-enabled Unmanned Aerial Vehicles (UAVs) provide potential supplementary platforms to assist air-to-ground cooperative communication. This paper investigates a joint safety information interaction scheme for a UAV-enabled network, which involves the complex constraints of three-dimensional trajectory planning, average energy efficiency optimization, and physical-layer security. Specifically, by modeling the UAV and the Ground Station (GS) as the transmit sources, we define the secure Energy Efficiency (EE) as the ratio of the total secrecy rate to the energy consumption of the whole system. Then, to achieve secure and energy-efficient communication in eavesdropping scenarios, we formulated the optimization problem as maximizing both the uplink/downlink secure EE of the system, subject to the constraints of the UAV’s mobility and the allowable transmit power. For this highly coupled non-convex problem, a composite solution of joint fractional programming, alternate optimization, the bisection method, and the interior-point method is proposed to obtain the achievable EE. Simulation and performance analysis gave the conclusions that the joint optimization of trajectory and power allocation is capable of maximizing the information secure EE. Additionally, the secure EE increases with the increase of the average transmit power, which finally tends to be stable.

The fusion of infrared and optical images is difficult because images of the intended infrared targets are weakened by the background of optical images when guided by traditional pixel-based fusing rules. In this study, an improved fusion method based on infrared target extraction is proposed. First, to highlight infrared targets in the fused image, this method obtains the target's contour binary image by Canny edge detection and obtains the segmented binary image by using Otsu threshold segmentation method. The proposed method then fuses the two binary images using their complementary information to generate a more complete infrared target image which guides the fusion of low-frequency coefficients of the source images. Second, the extracted infrared target image, the source infrared image, and the V component of the source optical image are all decomposed by Laplacian pyramid transform. High-frequency coefficient fusion is performed using the rules of region mutual information, region match measure, and region energy, meanwhile low-frequency coefficient fusion is performed using the infrared target image and region information rules. Experimental results indicate that the proposed fusion method outperforms traditional fusion methods in preserving infrared target information in the fused image.

Due to the malicious attacks in wireless networks, physical layer security has attracted increasing concerns from both academia and industry. The research on physical layer security mainly focuses either on the secrecy capacity/achievable secrecy rate/capacity-equivocation region from the perspective of information theory, or on the security designs from the viewpoints of optimization and signal processing. Because of its importance in security designs, the latter research direction is surveyed in a comprehensive way in this paper. The survey begins with typical wiretap channel models to cover common scenarios and systems. The topics on physical-layer security designs are then summarized from resource allocation, beamforming/precoding, and antenna/node selection and cooperation. Based on the aforementioned schemes, the performance metrics and fundamental optimization problems are discussed, which are generally adopted in security designs. Thereafter, the state of the art of optimization approaches on each research topic of physical layer security is reviewed from four categories of optimization problems, such as secrecy rate maximization, secrecy outrage probability minimization, power consumption minimization, and secure energy efficiency maximization. Furthermore, the impacts of channel state information on optimization and design are discussed. Finally, the survey concludes with the observations on potential future directions and open challenges.