Cooperative communications enabled by unmanned aerial vehicles (UAVs) can enlarge the transmission distance and coverage area. However, there is a serious issue of information security in UAV-cooperative wireless networks due to the broadcast feature of air-to-ground wireless channel. The framework of physical layer security provides an alternative technology to cope with this problem. Therefore, based on physical layer security, this paper focuses on maximizing the secrecy rate of a UAV-cooperative wireless networks by allocating the optimal power to the transmitter and the UAV. To deal with the difficulties of the resulting optimization problem, difference of convex (DC) programming is introduced to transform the primal problem into a series of convex subproblems which can be solved iteratively by some available convex optimization algorithm. Simulation results demonstrate that the proposed optimal power allocation algorithm can achieve a higher secrecy rate than the maximum power allocation algorithm does.
Cooperative communications enabled by unmanned aerial vehicles (UAVs) can enlarge the transmission distance and coverage area. However, there is a serious issue of information security in UAV-cooperative wireless networks due to the broadcast feature of air-to-ground wireless channel. The framework of physical layer security provides an alternative technology to cope with this problem. Therefore, based on physical layer security, this paper focuses on maximizing the secrecy rate of a UAV-cooperative wireless networks by allocating the optimal power to the transmitter and the UAV. To deal with the difficulties of the resulting optimization problem, difference of convex (DC) programming is introduced to transform the primal problem into a series of convex subproblems which can be solved iteratively by some available convex optimization algorithm. Simulation results demonstrate that the proposed optimal power allocation algorithm can achieve a higher secrecy rate than the maximum power allocation algorithm does.
The broadcast nature of air-to-ground line-of-sight (LoS) wireless channel imposes a great challenge in secure unmanned aerial vehicle (UAV) communications. To address this issue, this paper investigates UAV-ground communications from the physical-layer security perspective. Specifically, the investigated scenario includes a UAV serving as the base station (BS) that transmits confidential signals to a legitimate ground user, and there are multiple eavesdroppers on the ground with unknown position information. To further enhance the secrecy performance of the UAV-ground communications, an idle UAV can be employed to serve as a friendly jammer, which can transmit jamming signals to confuse the eavesdroppers. In our proposed strategy, the flying trajectory and the transmit power for both the UAVs are jointly optimized by maximizing the worst-case secrecy rate (WCSR) of the system. Considering the intractability of the formulated non-convex problem, we further provide a block coordinate descent-based iterative optimization method. Simulations verify that our proposed algorithm can significantly improve the average WCSR in comparison with the existing works.
Although unmanned aerial vehicles (UAVs) are enabling various applications in military, public, and commercial fields, the issue of information security in UAV communications is a critical issue which hinder the extensive applications of the UAVs. To cope with this issue, physical layer security is an alternative security technology, which can enhance the information security by flexibly adjusting transmission strategies and parameters to accommodate the channel changes. In this paper, the information security of the UAV communications is investigated from the perspective of physical layer security. The ground-to-air communications are considered under the presence of eavesdroppers, while the UAV can operate in a full-duplex mode so that it can perform cooperative jamming to confuse the eavesdroppers. The achievable secrecy rate of the UAV networks is maximized by the joint designs of the transmit precoding and cooperative jamming. To this end, an intractable optimization problem is formulated, and a solution scheme is proposed by using the approaches of equivalent transformation and alternating optimization. Simulation results demonstrate that the proposed scheme achieves a notable improvement in secrecy rate.
Cognitive unmanned aerial vehicle (UAV) communication systems combine benefits of both the cognitive radio and UAV, which improves the spectral efficiency and communication coverage area. However, high-quality air-ground channel links maybe more vulnerable to potential eavesdropping or jamming attacks. Thus, this paper proposes a secure transmission approach assisted by deploying a cooperative UAV to transmit artificial noise to jam an active eavesdropper, in order to maximize the system secrecy rate under the quality of service (QoS) requirement of a primary device. Specifically, we jointly optimize the flight trajectory and transmission power of the cooperative jammer to maximize the system's secrecy rate under strict constraints. To achieve this, we convert the non-convex problem into an approximately convex problem using the block coordinate descent algorithm and successive convex approximation method. Simulation results show that compared to existing algorithms, the proposed algorithm in this study can significantly improve the system's secrecy rate.
The broadcast nature of wireless channels introduces significant security vulnerabilities in information transmission, particularly when the eavesdropper is close to the legitimate destination. In such scenarios, the eavesdropping channel often exhibits high spatial correlation with, or even superior quality to, the legitimate channel. This makes it challenging for traditional power optimization methods to effectively suppress the eavesdropping rate. To address this challenge, this paper proposes an optimization method for the secrecy capacity of unmanned aerial vehicle (UAV) relaying based on the dynamic adjustment of the power allocation factor. By injecting artificial noise (AN) during signal forwarding and combining it with real-time channel state information, the power allocation factor can be dynamically adjusted to achieve precise jamming of the eavesdropping link. We consider a four-node communication model consisting of a source, a UAV, a legitimate destination, and a passive eavesdropper, and formulate a joint optimization problem to maximize the secrecy rate. Due to the non-convexity of the original problem, we introduce relaxation variables and apply successive convex approximation (SCA) to reformulate it into an equivalent convex optimization problem. An analytical solution for the power allocation factor is derived using the water-filling (WF) algorithm. Furthermore, an alternating iterative optimization algorithm with AN assistance is proposed to achieve global optimization of the system parameters. Simulation results demonstrate that, compared to traditional power optimization schemes, the proposed algorithm substantially suppresses the eavesdropping channel capacity while enhancing transmission efficiency, thereby significantly improving both secrecy performance and overall communication reliability.
This paper considers the use of an unmanned aerial vehicle (UAV) as a mobile relay to enhance the physical layer security in wireless wiretap channels. Specifically, we consider a scenario where a source (Alice) transmits signals to a destination (Bob) with the aid of the UAV in the presence of an eavesdropper (Eve). It is assumed that the UAV is able to cache the data received from Alice and then send to Bob in a secret fashion. Joint optimization of the communication resources and the UAV trajectory for maximizing the accumulated secrecy rate is investigated. While the joint design problem is non-convex, we propose an iterative algorithm based on successive convex approximation. Simulation results are presented to provide the insights into the proposed resource allocation strategy and trajectory for secure rate maximization and demonstrate how the UAV-aided rely can significantly enhance secrete rate transmissions.
This paper investigates an average secrecy rate (ASR) maximization problem for an unmanned aerial vehicle (UAV) enabled wireless communication system, wherein a UAV is employed to deliver confidential information to a ground destination in the presence of a terrestrial passive eavesdropper. By employing an artificial noise (AN) injection based secure two-phase transmission protocol, we aim at jointly optimizing the UAV’s trajectory, network transmission power, and AN power allocation over a given time horizon to enhance the ASR performance. Specifically, we divide the original non-convex problem into four subproblems, and propose a successive convex approximation based efficient iterative algorithm to solve it suboptimally with guaranteed convergence. Simulation results demonstrate significant security advantages of our designed scheme over other known benchmarks, particularly for stringent flight durations.