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IEEE Open Journal of the Communications Society

Robust Secrecy Energy Efficiency in UAV-Assisted Networks With Cooperative Aerial Jamming Against Aerial Eavesdroppers

Emmanouel T. Michailidis, Nikolaos I. Miridakis, Demosthenes Vouyioukas

Published Jan 1, 2026• 0 citations
Publisher

Abstract

This paper investigates a security-aware design for unmanned aerial vehicle (UAV)-assisted communication networks in adversarial environments with multiple aerial eavesdroppers (AEs) whose locations are imperfectly known. To enhance physical layer security (PLS), multiple cooperative aerial jammers (AJs) transmit artificial noise (AN), aiming to suppress the interception capability of AEs. Imperfect channel state information (CSI) is modeled via bounded small-scale fading errors, and location uncertainty of AEs is characterized by bounded spherical regions, enabling a deterministic worst-case secrecy rate formulation. Based on these uncertainty models, a worst-case robust secrecy energy efficiency (SEE) metric is defined as the ratio between the aggregate worst-case secrecy rate and the total energy consumption. Given the non-convex nature of this problem, a tractable solution framework is developed based on Dinkelbach’s method, block coordinate descent (BCD), and successive convex approximation (SCA). Simulation results reveal the benefits of cooperative multi-AJ operation in enhancing secrecy robustness against CSI errors and location uncertainty of AEs while maintaining energy efficiency.

DOI
10.1109/ojcoms.2026.3697830

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This paper investigates a security-aware design for unmanned aerial vehicle (UAV)-assisted communication networks in adversarial environments with multiple aerial eavesdroppers (AEs) whose locations are imperfectly known. To enhance physical layer security (PLS), multiple cooperative aerial jammers (AJs) transmit artificial noise (AN), aiming to suppress the interception capability of AEs. Imperfect channel state information (CSI) is modeled via bounded small-scale fading errors, and location uncertainty of AEs is characterized by bounded spherical regions, enabling a deterministic worst-case secrecy rate formulation. Based on these uncertainty models, a worst-case robust secrecy energy efficiency (SEE) metric is defined as the ratio between the aggregate worst-case secrecy rate and the total energy consumption. Given the non-convex nature of this problem, a tractable solution framework is developed based on Dinkelbach’s method, block coordinate descent (BCD), and successive convex approximation (SCA). Simulation results reveal the benefits of cooperative multi-AJ operation in enhancing secrecy robustness against CSI errors and location uncertainty of AEs while maintaining energy efficiency.
The rapid development of Uncrewed Aerial Vehicle (UAV)-enabled wireless networks has greatly enhanced communication flexibility and connectivity in challenging and security-sensitive scenarios. However, achieving high communication security and energy efficiency remains difficult, especially when the locations of potential eavesdroppers are uncertain and time-varying. Existing studies on UAV-enabled secure communications have advanced Secrecy Energy Efficiency (SEE)-oriented design from multiple perspectives, but the joint integration of cooperative dual-UAV design, cooperative jamming, bounded eavesdropper-location uncertainty, and robust SEE maximization remains insufficiently explored. To address this issue, we investigate a cooperative UAV-enabled secure communication system in which a source UAV transmits confidential data to a legitimate user with the assistance of a jammer UAV. We formulate a robust SEE maximization problem under bounded eavesdropper-location uncertainty and develop an efficient solution framework based on alternating optimization, Successive Convex Approximation (SCA), the S-procedure, and Dinkelbach’s method. Simulation results demonstrate that the proposed method achieves superior SEE and stronger robustness against eavesdropper-location uncertainty compared with benchmark schemes.
This paper exploits the mobility of an unmanned aerial vehicle (UAV) to improve the physical layer (PLS) security against potential eavesdropping scenarios, where the sensitive data transmitted from a ground base station (GBS) to multiple information receivers (IRs) is easily eavesdropped by multiple non-colluding eavesdroppers (Eves). Specifically, the UAV is employed as a friendly jammer to transmit artificial noise to degrade the wiretap channels. By leveraging the UAV's mobility and the possibility of establishing line-of-sight links, the UAV can move close to the Eves and opportunistically jam them. Especially, two practical factors, namely, the imperfect location information of Eves and the existence of no-fly zones are considered. Since only the partial position information of the Eves can be known, as the worst case, the minimum average secrecy rate of IRs is robustly optimized by jointly designing the trajectory and jamming power of the UAV, and the transmission power of the GBS to ensure the security of all IRs. However, the formulated problem with coupled variables is non-convex and intractable. As such, an efficient alternative iterative suboptimal algorithm is proposed to solve this problem by applying the block coordinate descent, successive convex approximation, slack variables, andS\mathcal {S}S-Procedure. Numerical results reveal that the proposed robust algorithm can substantially improve the max-min average secrecy rate, and the effectiveness of the proposed algorithm is further verified by comparing it with three benchmark schemes.
This paper investigates the jointly transmit power and unmanned aerial vehicle (UAV)/jammer deployment optimization problem for UAV enabled jammer-assisted secure communication systems, where a jammer is exploited to assist transmitting data from a source node to a legitimate destination node in the presence of multiple eavesdroppers. To increase the secrecy energy efficiency, which is defined as the achievable secrecy rate per energy consumption unit, we formulate a secrecy energy efficiency maximization problem by jointly optimizing the transmit power and UAV/jammer deployment. The resulting optimization problem is shown to be a non-convex and fractional optimization problem, which is challenging to solve. As such, we decompose the original problem into two sub-problems, and then, an efficient iterative algorithm is proposed by leveraging the extensive search method and Dinkelbach method in combination with successive convex approximation (SCA) techniques. Numerical simulation results show that the proposed scheme significantly improves the secrecy energy efficiency of the system.
In this paper, we study secure cooperative transmission for the multiple-input-single-output multiple-eavesdropper (MISOME) systems, where a source (Alice) aims to send confidential messages to a legitimate user (Bob) with the aid of an unmanned aerial vehicle (UAV) enabled friendly jammer (Charlie) in the presence of multiple eavesdroppers (Eves). To further guarantee the secrecy performance, artificial noise (AN) beamforming together with cooperative Jamming (CJ) has been utilized in this considered system with only location and statistical channel state information of the Eves. Specifically, taking imperfect channel state information (CSI) between Charlie and Bob into account, we derive the exact closed-form expression of the secrecy outage probability (SOP) and develop an efficient scheme to solve the secrecy rate maximization (SRM) problem which has been verified as a convex one under certain SOP. Moreover, we propose an optimal UAV placement strategy to further enhance secrecy performance. The numerical results are provided to validate that the system security would seriously degenerate with channel uncertainty. Besides, the proposed scheme is verified to outperform the terrestrial CJ scheme in improving the secrecy rate and secure energy efficiency (EE) performance under perfect CSI or tolerable channel estimation errors. Finally, the effectiveness of the proposed UAV placement strategy in enhancing transmission security and the applicability of the proposed scheme has also been demonstrated.
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.
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.