This paper investigates a novel unmanned aerial vehicles (UAVs) secure communication system with the assistance of reconfigurable intelligent surfaces (RISs), where a UAV and a ground user communicate with each other, while an eavesdropper tends to wiretap their information. Due to the limited capacity of UAVs, an RIS is applied to further improve the quality of the secure communication. The time division multiple access (TDMA) protocol is applied for the communications between the UAV and the ground user, namely, the downlink (DL) and the uplink (UL) communications. In particular, the channel state information (CSI) of the eavesdropping channels is assumed to be imperfect. We aim to maximize the average worst-case secrecy rate by the robust joint design of the UAV’s trajectory, RIS’s passive beamforming, and transmit power of the legitimate transmitters. However, it is challenging to solve the joint UL/DL optimization problem due to its non-convexity. Therefore, we develop an efficient algorithm based on the alternating optimization (AO) technique. Specifically, the formulated problem is divided into three sub-problems, and the successive convex approximation (SCA), $\mathcal {S}$ -Procedure, and semidefinite relaxation (SDR) are applied to tackle these non-convex sub-problems. Numerical results demonstrate that the proposed algorithm can considerably improve the average secrecy rate compared with the benchmark algorithms, and also confirm the robustness of the proposed algorithm.

Unmanned aerial vehicle (UAV) and reconfigurable intelligent surface (RIS) have been recently applied in the field of mobile edge computing (MEC) to improve the data exchange environment by proactively changing the wireless channels through maneuverable location deployment and intelligent signals reflection, respectively. Nevertheless, they may suffer from inherent limitations, e.g., UAV’s low endurance and RIS’s finite coverage, which limit their wider applications. UAV-mounted RIS (U-RIS), as a promising integrated approach, can combine the advantages of UAV and RIS to break the limit. Inspired by this, we consider a novel U-RIS assisted MEC system, where a U-RIS is deployed to assist the communication between the ground users and an MEC server. The joint UAV trajectory, RIS passive beamforming and MEC resource allocation design is developed to maximize the energy efficiency (EE) of the system. To tackle the intractable non-convex problem, we divide it into two subproblems and solve them iteratively based on successive convex approximation (SCA) and the Dinkelbach method. Finally we obtain a high-performance suboptimal solution. Simulation results show that the proposed algorithm significantly improves the energy efficiency of the MEC system.

This paper investigates the anti-jamming three-dimensional (3D) trajectory design to safeguard the legitimate communications of unmanned aerial vehicle (UAV)-enabled wireless sensor networks (WSNs). Specifically, a UAV is dispatched to collect data over multiple ground sensors (GSs) in the presence of a malicious ground jammer. Under the practical probabilistic line-of-sight (LoS) channel model, we aim to maximize the minimum (average) expected rate among GSs over a finite flight period, by jointly optimizing the GS transmission scheduling, the UAV horizontal and vertical trajectories. To make the formulated non-convex problem tractable, we provide an achievable lower bound for the expected rate, based on which an efficient iterative algorithm is proposed to solve it suboptimally by exploiting the block coordinate descent and successive convex approximation techniques. Numerical results show the significant rate improvement of the proposed joint design and provide new insights into the anti-jamming 3D trajectory design under the probabilistic LoS model, as compared to the conventional two-dimensional (2D) UAV trajectory or under LoS channel models.

This paper proposes a new full-duplex (FD) secrecy communication scheme for the unmanned aerial vehicle (UAV) and investigates its optimal design to achieve the maximum energy efficiency (EE) of the UAV. Specifically, the UAV receives the confidential information from a ground source and meanwhile sends jamming signals to interfere with a potential ground eavesdropper. As the UAV has limited on-board energy in practice, we aim to maximize the EE for its secrecy communication, by jointly optimizing the UAV trajectory and the source/UAV transmit/jamming powers over a finite flight period. Although the formulated problem is difficult to be optimally solved due to its non-convexity, we propose an efficient iterative algorithm to obtain its high-quality suboptimal solution. Simulation results show that significant EE improvements can be achieved via joint optimization and the EE gains highly depend on the capability of the self-interference cancelation at the UAV.

This letter proposes a generalised propulsion energy consumption model (PECM) for rotary-wing unmanned aerial vehicles (UAVs) under the consideration of the practical thrust-to-weight ratio (TWR) with respect to the velocity, acceleration and direction change of the UAVs. To verify the effectiveness of the proposed PECM, we consider a UAV-enabled communication system, where a rotary-wing UAV serves multiple ground users as an aerial base station. We aim to maximize the energy efficiency (EE) of the UAV by jointly optimizing the user scheduling and UAV trajectory variables. However, the formulated problem is a non-convex fractional integer programming problem, which is challenging to obtain its optimal solution. To tackle this problem, we propose an efficient iterative algorithm by decomposing the original problem into two sub-problems to obtain a suboptimal solution based on the successive convex approximation technique. Simulation results show that the optimized UAV trajectory by applying the proposed PECM are smoother and the corresponding EE has significant improvement as compared to other benchmark schemes.