Artificial-Noise-Aided Secure Transmission Optimization Method for UAV Relay Communications

CHEN Xiaoxuan; PENG Laixian; WEI Jianyu; XU Renhui; XU Zhengqin; WANG Haichao

doi:10.11999/JEIT261122

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CHEN Xiaoxuan, PENG Laixian, WEI Jianyu, XU Renhui, XU Zhengqin, WANG Haichao. Artificial-Noise-Aided Secure Transmission Optimization Method for UAV Relay Communications[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT261122

Citation:

CHEN Xiaoxuan, PENG Laixian, WEI Jianyu, XU Renhui, XU Zhengqin, WANG Haichao. Artificial-Noise-Aided Secure Transmission Optimization Method for UAV Relay Communications[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT261122

Citation:

CHEN Xiaoxuan, PENG Laixian, WEI Jianyu, XU Renhui, XU Zhengqin, WANG Haichao. Artificial-Noise-Aided Secure Transmission Optimization Method for UAV Relay Communications[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT261122

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Artificial-Noise-Aided Secure Transmission Optimization Method for UAV Relay Communications

doi: 10.11999/JEIT261122 cstr: 32379.14.JEIT261122

1.
Army Engineering University of PLA, Nanjing 210007, China
2.
PAP Command College, Tianjin 300250, China

Funds: The National Natural Science Foundation of China (62271501, 62521003, 62671617), The Natural Science Foundation of Jiangsu Province(BK20240200), The Key Technologies R&D Program of Jiangsu (Prospective and Key Technologies for Industry) (BE2023022, BE2023022-4)

Accepted Date: 2026-11-05
Rev Recd Date: 2026-11-05

Available Online: 2026-11-14

Abstract

Abstract

Objective When the direct links between a ground base station (BS) and the user equipments (UEs) are unavailable because of blockage, an unmanned aerial vehicle (UAV) can be deployed as an amplify-and-forward (AF) aerial relay to improve the transmission conditions between the BS and legitimate UEs. However, the predominantly line-of-sight (LoS) propagation of air–ground links may enhance not only the legitimate links but also the signal reception at an eavesdropper, thereby increasing the risk of information leakage. Existing studies on physical-layer security in UAV relay communications have primarily focused on single-user or single-antenna scenarios, whereas joint interference management and secure transmission in multi-user multi-antenna systems remain insufficiently investigated. Moreover, only subsets of the design variables are typically jointly optimized, and the coupling among UAV placement, information transmission, and jamming resource allocation has not been adequately addressed. Therefore, an artificial-noise-aided secure transmission optimization method is proposed for UAV relay communications. Null-space artificial-noise (AN) is designed, and the UAV position, BS precoding, and AN are jointly optimized to maximize the system sum secrecy rate. Methods A secure UAV relay communication model is established, consisting of a ground BS, a UAV relay, multiple legitimate UEs, and one passive eavesdropper, denoted as Eve. The direct links between the BS and all ground nodes are assumed to be unavailable. The UAV moves at a fixed altitude and employs an ideal full-duplex scalar AF protocol. The BS transmits information through linear precoding while simultaneously injecting AN to suppress the eavesdropping link. To eliminate the direct interference caused by AN to the legitimate UEs, the AN is projected onto the null space of the cascaded channels associated with the legitimate UEs. A joint optimization problem involving the UAV position, BS precoding, and AN design is then formulated to maximize the system sum secrecy rate. Because the optimization variables are highly coupled and the resulting problem is nonconvex, an alternating optimization (AO) framework is developed. The original problem is decomposed into a UAV position optimization subproblem and a joint BS precoding and AN design subproblem. For the UAV position optimization subproblem, a multi-strategy improved particle swarm optimization (MSIPSO) algorithm is employed to determine a near-optimal hovering position. For the joint BS precoding and AN design subproblem, successive convex approximation (SCA) and semidefinite relaxation (SDR) are applied to transform the nonconvex objective function and constraints into tractable convex forms. The resulting problem is solved iteratively to obtain a feasible approximate solution that satisfies the system constraints. Results and Discussions The simulation results demonstrate that the proposed algorithm achieves a higher system sum secrecy rate than the benchmark schemes, including the fixed-UAV-position scheme, the scheme without AN, the zero-forcing null-space AN (ZF-NSAN) scheme, and the maximum-ratio-transmission null-space AN (MRT-NSAN) scheme. Moreover, its performance improves as the number of users increases, validating the effectiveness of jointly optimizing the UAV position, BS precoding, and AN design for multi-user secure transmission (Fig. 3). The fixed-UAV-position scheme cannot fully exploit the spatial deployment flexibility of the UAV, whereas the scheme without AN lacks an active mechanism for suppressing the eavesdropping link. In addition, the ZF-NSAN and MRT-NSAN schemes employ predetermined information precoding structures and therefore cannot jointly configure the information precoding and the AN design. By contrast, the proposed algorithm jointly optimizes the UAV position, BS precoding, and AN design. Consequently, the spatial deployment flexibility and multi-antenna resources are more effectively utilized to strengthen the legitimate links while suppressing the eavesdropping link. As the transmit power of the BS or UAV increases, the system sum secrecy rate achieved by all schemes generally increases. The proposed algorithm consistently maintains its performance advantage, indicating that joint resource optimization enables more efficient allocation of the available transmit power. However, the improvement in the sum secrecy rate gradually diminishes in the high-power regime. This result indicates that an increase in transmit power may also strengthen the eavesdropping link. Therefore, a substantial and sustained security gain cannot be achieved solely by increasing the transmit power (Figs. 4 & 5). As the number of BS transmit antennas increases, the null-space dimension available for AN transmission is enlarged for a fixed number of legitimate users, thereby enhancing the system security performance (Fig. 6). Meanwhile, increasing the number of UAV receive antennas improves the receive array gain and spatial combining capability, leading to a higher system sum secrecy rate. However, the performance gain gradually saturates when the number of receive antennas becomes sufficiently large (Fig. 7). These results verify the effectiveness of jointly optimizing the UAV position, BS precoding, and AN design in improving the physical-layer security performance of the system. Conclusions To address the physical-layer security problem in UAV relay communication systems where the direct links between the ground BS and the UEs are blocked, an AN-aided secure transmission optimization method is proposed. The UAV position, BS precoding, and AN design are incorporated into a unified system sum secrecy rate maximization framework. Through their coordinated optimization, the spatial deployment flexibility of the UAV and the multi-antenna resources of the BS are jointly exploited. As a result, the transmission quality of the legitimate links is improved, while the eavesdropper’s capability to intercept confidential information is suppressed. The simulation results confirm that the joint optimization of the UAV position, BS precoding, and AN design effectively enhances the secure transmission performance of the system. The proposed method provides a feasible resource optimization approach for information security in UAV relay communications. Future studies may further consider imperfect channel state information, residual self-interference at the full-duplex UAV, dynamic UAV trajectory optimization, and multiple eavesdroppers to improve the applicability of the proposed method to more general secure communication scenarios.
- Physical layer security,
- Unmanned Aerial Vehicle (UAV),
- Artificial noise (AN),
- Joint resource optimization

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References(28)

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