面向低空异构恶意实体的智能超表面辅助通感一体化

RIS-Assisted ISAC Against Heterogeneous Malicious Entities in Low-Altitude Environments

  • 摘要: 联合设计发射波束赋形与可重构智能超表面(reconfigurable intelligent surfaces,RIS)相移矩阵是无人机辅助通感一体化系统中的关键任务。然而,现有工作未充分考虑低空活动中空间分布多样且功能异构的恶意实体共存的复杂安全环境。受此启发,提出一种新型鲁棒RIS辅助通感一体系统,该系统综合考虑地面被动窃听者、空中主动干扰机以及空中混合型主被动恶意实体。为应对安全威胁,采用人工噪声干扰机制降低窃听者接收质量,同时利用RIS增强机制提升有用信号功率以对抗恶意干扰,针对混合型恶意实体同时采用上述两种机制。构建联合发射波束赋形与RIS相移矩阵设计优化问题,旨在通信信干噪比与安全信干噪比约束下最大化感知信杂噪比。为求解该非凸问题,采用多种数学技术,包括主化最小化算法与半定松弛法。仿真结果验证了所提算法的有效性,且在安全信干噪比约束下,所提人工噪声干扰机制与RIS增强机制分别提升感知信杂噪比约49.75%与22.58%。

     

    Abstract: Joint transmit beamforming and reconfigurable intelligent surface (RIS) phase-shift matrix design is an essential task in uncrewed aerial vehicle (UAV)-assisted integrated sensing and communication (ISAC) systems. However, existing works mainly neglect the complex security environment where spatially diverse and functionally heterogeneous malicious entities coexist in low-altitude activities. Motivated by this, we propose a novel robust RIS-assisted ISAC system where ground passive eavesdroppers, aerial active jammers, and aerial hybrid active-passive malicious users are comprehensively incorporated. To mitigate these security threats, we employ an artificial noise interference (ANI) mechanism to degrade the reception quality of eavesdroppers, while utilizing the RIS enhancement mechanism to enhance the intended signal power against jamming interference. For hybrid malicious users, both mechanisms are simultaneously adopted. An optimization of joint transmit beamforming and RIS phase-shift matrix design is established to maximize the sensing signal-to-clutter-plus-noise ratio (SCNR), subject to communication signal-to-interference-plus-noise ratio (SINR) and security SINR. To tackle this non-convex problem, various mathematical techniques are adopted, including majorization-minimization and semidefinite relaxation. Experiment results demonstrate the effectiveness of the proposed algorithm. In addition, the proposed ANI mechanism and RIS enhancement mechanism increase the sensing SCNR by approximately 49.75% and 22.58% under the security SINR constraints, respectively.

     

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