对抗动态窃听的空天地网络上行安全传输-“空天地一体化智能网联”专刊

  • 张云阳 ,
  • 王礴航 ,
  • 丁国如
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  • 1. 航天工程大学
    2. 陆军工程大学

收稿日期: 2025-12-05

  修回日期: 2026-01-14

  网络出版日期: 2026-01-15

基金资助

国家自然科学基金;国家自然科学基金;国家自然科学基金

Uplink Secure Transmission in Space-Air-Ground Integrated Networks Against Dynamic Eavesdropping

  • ZHANG Yun-Yang ,
  • WANG Bo-Hang ,
  • DING Guo-Ru
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Received date: 2025-12-05

  Revised date: 2026-01-14

  Online published: 2026-01-15

摘要

无线通信网络的安全与隐私保护是6G空天地一体化发展进程中的关键挑战。为应对立体覆盖、多域协同等复杂场景下所面临的多元窃听威胁,该研究提出了一种面向空天地网络的上行安全传输框架。系统模型包含四类核心节点:卫星、合法中继无人机(Relay Unmanned Aerial Vehicle,R-UAV)、非法窃听无人机(Eavesdropping Unmanned Aerial Vehicle,E-UAV)与地面用户。其中,卫星仅接收来自R-UAV的中继信号,以模拟潜在的恶劣信道条件与协同通信应用需求;E-UAV在通信空域内巡航,并伺机截获用户上行信息。针对该场景,研究基于公平性准则构建系统安全传输速率最大化问题,并提出了一种联合块坐标下降法、半正定松弛、序贯凸近似与双深度Q网络的协同优化算法,对无人机飞行轨迹、资源分配策略与波束成形参数进行联合设计,以平衡系统安全与通信性能。仿真结果表明,所提方法在动态窃听环境中具有良好的灵活性与安全传输优势,并揭示了R-UAV承载资源、硬件配置与系统性能之间的内在关系。

本文引用格式

张云阳 , 王礴航 , 丁国如 . 对抗动态窃听的空天地网络上行安全传输-“空天地一体化智能网联”专刊[J]. 航空学报, 0 : 1 -0 . DOI: 10.7527/S1000-6893.2026.33199

Abstract

The security and privacy of wireless communication networks constitute a critical challenge in the evolution toward 6G-enabled space-air-ground integrated networks. To address sophisticated eavesdropping threats in complex scenarios characterized by three-dimensional coverage and multi-domain collaboration, this study proposes an uplink secure transmission framework for space-air-ground integrated networks. The system model encompasses four core entities: a satellite, a legitimate relay unmanned aerial vehicle (R-UAV), a malicious eavesdropping UAV (E-UAV), and terrestrial users. The satellite is configured to receive relayed signals solely from the R-UAV, modeling harsh channel conditions or application-specific cooperative communication requirements. The E-UAV cruises within the communication airspace, attempting to opportunistically intercept the users’ uplink transmissions. For this dynamic scenario, we formulate a system secrecy rate maximization problem based on a fairness criterion. To solve this highly non-convex and coupled problem, a cooperative optimization algorithm integrating block coordinate descent, semidefinite relaxation, successive convex approximation, and a dual deep Q-network is proposed. This algorithm jointly designs the UAV’s flight trajectory, resource allocation strategy, and beamforming parameters to balance security and communication performance. Simulation results demonstrate that the proposed method offers superior flexibility and security advantages in dynamic eavesdropping environments. Furthermore, the analysis elucidates the intrinsic trade-off between the R-UAV’s onboard resources, hardware configuration, and overall system performance.

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