面向无人机可见光通信系统的安全隐蔽传输策略研究

吴梦如; 林嘉乐; 卢为党; 李博; 郭磊

doi:10.11999/JEIT260239

面向无人机可见光通信系统的安全隐蔽传输策略研究

doi: 10.11999/JEIT260239 cstr: 32379.14.JEIT260239

1.
浙江工业大学信息工程学院杭州 310023
2.
哈尔滨工业大学(威海)信息科学与工程学院威海 264209
3.
东北大学计算机科学与工程学院沈阳 110819

基金项目: 国家自然科学基金(No.62301490, No.62271447)，浙江省自然科学基金(No.LR25F010003, No.LQ24F010013)

详细信息

作者简介:
吴梦如：女，讲师，研究方向为移动边缘计算、无人机通信、安全通信等

林嘉乐：男，硕士生，研究方向为无人机通信、隐蔽通信等

卢为党：男，教授，博士生导师，研究方向为智能通信、无人机通信、安全通信等

李博：男，教授，博士生导师，研究方向为空天地海一体化信息网络、6G移动通信等

郭磊：男，教授，博士生导师，研究方向为光通信网络、无线通信网络等

通讯作者:
卢为党　luweid@zjut.edu.cn

中图分类号: TN929.1
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- 被引次数: 0
出版历程
- 修回日期: 2026-04-23
- 录用日期: 2026-04-23
- 网络出版日期: 2026-05-23

Research on Secure and Covert Transmission for UAV-Assisted Visible Light Communication Systems

WU Mengru¹,
LIN Jiale¹,
LU Weidang^{1
, ,},
LI Bo²,
GUO Lei³

1.
College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
2.
School of Information Science and Engineering, Harbin Institute of Technology, Weihai 264209, China
3.
School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China

Funds: The National Natural Science Foundation of China (No.62301490, No.62271447), The Natural Science Foundation of Zhejiang Province (No.LR25F010003, No.LQ24F010013)

摘要

摘要: 无人机(UAV, unmanned aerial vehicle)因自身的机动性和按需覆盖能力，可作为空中基站实现空地之间的可见光通信(VLC, visible light communication)。然而，空地之间的通信链路暴露在开放环境中，这使得VLC容易受到数据窃听和恶意检测。针对此问题，从物理层安全和隐蔽通信的角度提出了面向UAV的VLC系统中的安全隐蔽传输策略。该策略在考虑隐蔽通信要求、照明目标要求、UAV发射功率和悬停高度限制的基础上，对UAV发射功率和部署高度进行了联合优化以最大化系统的保密容量。由于所构建的优化问题高度非凸，因此设计了基于粒子群优化的双层优化算法对该问题进行求解。仿真结果表明，所提算法能够较快收敛，并且相较于基准方案能够提高系统的保密性能。
- 无人机 /
- 可见光通信 /
- 物理层安全 /
- 隐蔽通信
Abstract: Objective Owing to mobility and on-demand coverage capabilities, unmanned aerial vehicles (UAVs) can serve as aerial base stations to enable visible light communication (VLC). However, air-ground communication links are exposed to open environments, making VLC vulnerable to data eavesdropping and malicious detection. To address this issue, this paper proposes a secure and covert transmission strategy for a UAV-assisted VLC system from the perspectives of physical layer security and covert communication. The proposed strategy jointly optimizes the transmit power and hovering altitude of a UAV to maximize the system’s secrecy capacity, subject to the requirements of covert communication and illumination targets, as well as the operational constraints on UAV transmit power and hovering altitude. Methods This paper investigates secure and covert communication for UAV-assisted VLC. First, a UAV-assisted VLC system model is proposed, in which a mobile UAV equipped with light-emitting diodes is employed to establish a VLC link with a ground user in the presence of an eavesdropper and a warden. Subsequently, an optimization problem is formulated to maximize the secrecy capacity of the system by jointly optimizing the transmit power and hovering altitude of the UAV. To solve the formulated problem, we propose a two-layer optimization (TLOP) algorithm to decompose the transformed problem into two subproblems, including an inner-layer subproblem for transmit power optimization and an outer-layer subproblem for the design of UAV hovering altitude. On this basis, a closed-form expression for the optimal transmit power is derived for the inner-layer problem, while a particle swarm optimization (PSO) algorithm is developed to solve the outer-layer problem. Results and Discussions In the simulations, the proposed optimization scheme is compared with two baselines. First, the convergence of the proposed TLOP algorithm is verified (Fig. 3). The results demonstrate that the algorithm achieves rapid convergence within a limited number of iterations. Second, the optimal hovering altitude of the UAV with respect to the UAV’s horizontal coordinates under spatial distribution is illustrated (Fig. 4). The results indicate that as the UAV gradually approaches the ground legitimate user, its optimal hovering altitude exhibits a downward trend. Then, the secrecy capacity with respect to the UAV’s horizontal coordinates is presented (Fig. 5). It can be clearly observed that the secrecy capacity shows an upward trend as the UAV approaches the ground legitimate user. This is because as the UAV gets closer to the user, the constraints imposed by secure and covert communication are gradually relaxed. Furthermore, as $ \epsilon $ increases, the secrecy capacity of all schemes exhibits an increasing trend (Fig. 6). This is because the relaxation of covertness requirements enables the UAV to flexibly adjust its hovering altitude and transmit power to increase the secrecy capacity of the system. In addition, the secrecy capacity shows a declining trend as the number of symbols increases (Fig. 7). The reason can be attributed to the fact that the increase in the number of symbols provides the warden with more signal samples available for detection. Finally, the secrecy capacity of all schemes decreases as the uncertainty region radius of malicious users increases (Fig. 8). This trend is explained by the increased uncertainty requires the UAV to address potential threats over a wider area, which forces the UAV to adopt a more conservative strategy. In conclusion, simulation results confirm that the proposed scheme can improve the secrecy capacity of the UAV-assisted VLC system. Conclusions This paper investigates secure and covert communication in a UAV-assisted VLC system. Our goal is to maximize the secrecy capacity of the system by jointly optimizing the transmit power and hovering altitude of a UAV. Given that the formulated problem is a highly non-convex problem, a TLOP algorithm based on PSO is designed to solve it. Simulation results demonstrate that the proposed algorithm achieves fast convergence and improves the system’s secrecy performance compared to baselines.
- Unmanned Aerial Vehicle (UAV) /
- Visible Light Communication (VLC) /
- Physical Layer Security /
- Covert Communication.

HTML全文

图 1 面向UAV的VLC系统模型

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图 2 发射器和接收器之间的几何架构

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图 3 所提算法的收敛性能分析

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图 4 UAV最优悬停高度随UAV水平坐标的变化

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图 5 空间分布下保密容量值随UAV水平坐标的变化

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图 6 隐蔽需求与保密容量的关系

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图 7 总符号数与保密容量的关系

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图 8 不确定区域半径与保密容量的关系

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1 基于PSO的TLOP算法求解$ {\mathcal{P}}_{0} $

初始化：在$ [0,L] $范围内随机初始$ S $个UAV悬停高度　$ {H}_{u}{}^{(1)},{H}_{u}{}^{(2)},\cdots,{H}_{u}{}^{(S)} $。
(1) 循环
(2) 　给定$ {H}_{u}{}^{(s)} $，对$ {h}_{b}{}^{2}\sigma _{e}^{2}-h_{e}^{*}{}^{2}\sigma _{b}^{2}\gtrless 0 $进行判决；
(3) 　基于(33)求解以获得最优解$ p_{u}^{opt} $；
(4) 　给定$ p_{u}^{opt} $，基于(36)获得$ {H}_{u}{}^{(s)} $对应的适应度；
(5) 　根据适应度更新最优位置，基于(39)和(40)更新每个粒子　　　的速度和位置；
(6) 重复步骤(2)-步骤(5)，直到收敛。

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