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IEEE International Conference on Communication Technology (ICCT)

Physical Layer Security Enhancement Techniques for UAV Relay Systems Based on Artificial Noise Assistance

Yunqi Hao, Youyang Xiang, Xianglu Li, Chen Ding, Qilong Du, Dong Hou, Jie Tian

Published Oct 16, 2025• 0 citations
Publisher

Abstract

The broadcast nature of wireless channels introduces significant security risks during information transmission. When the eavesdropper is in close proximity to the legitimate receiver, their channel state information (CSI) may be highly correlated or even superior to that of the legitimate channel, rendering traditional power optimization methods ineffective in suppressing eavesdropping rates. To address this issue, this paper proposes an artificial noise (AN)-assisted unmanned aerial vehicle (UAV) relay system. By leveraging the UAV relay to inject artificial noise while transmitting signals and dynamically adjusting the power allocation factor based on real-time CSI and the UAV's position, precise interference control over the eavesdropping channel is achieved. This study establishes a fournode communication system comprising a source, relay, legitimate receiver, and eavesdropper, formulating a joint optimization problem aimed at maximizing secrecy capacity. Given the nonconvex nature of the optimization problem, this paper employs slack variables and the successive convex approximation (SCA) method to equivalently transform the original problem into a convex problem. A closed-form analytical solution for the power allocation factor is derived using the staircase water-filling (WF) algorithm. Furthermore, an alternating iterative optimization algorithm based on artificial noise assistance is proposed to achieve global optimization of system parameters. Simulation results demonstrate that, compared to traditional power optimization schemes, the proposed algorithm reduces the eavesdropping capacity and improves the information transmission efficiency, significantly enhancing both system security and transmission performance.

DOI
10.1109/icct67417.2025.11374271

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The broadcast nature of wireless channels introduces significant security risks during information transmission. When the eavesdropper is in close proximity to the legitimate receiver, their channel state information (CSI) may be highly correlated or even superior to that of the legitimate channel, rendering traditional power optimization methods ineffective in suppressing eavesdropping rates. To address this issue, this paper proposes an artificial noise (AN)-assisted unmanned aerial vehicle (UAV) relay system. By leveraging the UAV relay to inject artificial noise while transmitting signals and dynamically adjusting the power allocation factor based on real-time CSI and the UAV's position, precise interference control over the eavesdropping channel is achieved. This study establishes a fournode communication system comprising a source, relay, legitimate receiver, and eavesdropper, formulating a joint optimization problem aimed at maximizing secrecy capacity. Given the nonconvex nature of the optimization problem, this paper employs slack variables and the successive convex approximation (SCA) method to equivalently transform the original problem into a convex problem. A closed-form analytical solution for the power allocation factor is derived using the staircase water-filling (WF) algorithm. Furthermore, an alternating iterative optimization algorithm based on artificial noise assistance is proposed to achieve global optimization of system parameters. Simulation results demonstrate that, compared to traditional power optimization schemes, the proposed algorithm reduces the eavesdropping capacity and improves the information transmission efficiency, significantly enhancing both system security and transmission performance.
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 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.
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.
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This paper investigates secure communications between a pair of ground transceivers with the aid of a relay unmanned aerial vehicle (UAV). Specifically, we consider a powerful eavesdropper who conducts eavesdropping attacks in two transmission phases. The multi-antenna transmitter communicates with the UAV through information beamforming in Phase I, and the UAV relays the secrecy data through a single antenna to the receiver in Phase II. We propose a secure transmission scheme where the transmitter utilizes artificial noise technique to interfere with the eavesdropper through jamming beamforming in two phases. In particular, we formulate an optimization problem, and employ the max-min optimization, block coordinate descent, semi-definite relaxation, and successive convex approximation methods to deal with it. Simulation results verify the effectiveness and superiority of the proposed secure transmission scheme.
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.