This paper considers a hybrid reconfigurable environment comprising a UAV-mounted reflecting RIS, an outdoor STAR-RIS enabling simultaneous transmission and reflection, and an indoor holographic RIS (H-RIS), jointly enhancing secure downlink communication for indoor and outdoor users. The system operates under user mobility, dynamic blockages, colluding idle and active eavesdroppers, and transceiver and surface hardware impairments. A 3GPP and ITU-compliant stochastic channel model is developed, capturing mobility-induced covariance evolution, outdoor-indoor penetration losses, and distortion-aware noise due to practical EVM-based impairments. We aim to minimize the aggregate secrecy-outage probability subject to secrecy-rate constraints, QoS requirements, power limitations, and statistical CSI uncertainty. The resulting problem contains coupled secrecy and QoS chance constraints and nonlinear interactions among the BS beamforming vectors, multi-surface phase coefficients, and UAV position. To handle these difficulties, we derive rigorous Bernstein-type deterministic approximations for all chance constraints, yielding a distributionally robust reformulation. Building on this, we propose an alternating optimization framework that employs successive convex approximation (SCA) to convexify each block and solve the BS beamforming, RIS, STAR-RIS, H-RIS configuration, and UAV placement subproblems efficiently. The proposed algorithm is shown to monotonically decrease a smooth surrogate of the secrecy-outage cost and converge to a stationary point of the robustified problem. Simulations based on 3GPP TR 38.901, TR 36.873, and ITU-R P.2109 demonstrate that integrating UAV-RIS, STAR-RIS, and H-RIS significantly reduces secrecy-outage probability compared with benchmark schemes and provides strong robustness to channel uncertainty, blockages, colluding eavesdroppers, and hardware impairments.

翻译：本文研究一种混合可重构智能表面环境，该系统包含无人机搭载的反射型RIS、支持同时透射与反射的室外STAR-RIS以及室内全息RIS（H-RIS），共同为室内外用户提供增强的安全下行通信。系统在用户移动性、动态遮挡、空闲与活跃窃听者共谋、收发机及表面硬件损伤等复杂条件下运行。我们建立了符合3GPP与ITU标准的随机信道模型，该模型捕捉了移动性引起的协方差演化、室外-室内穿透损耗以及基于实际EVM损伤的失真感知噪声。研究目标是在满足保密速率约束、服务质量要求、功率限制及统计CSI不确定性的条件下，最小化总体保密中断概率。该优化问题包含耦合的保密性与服务质量机会约束，以及基站波束成形向量、多表面相位系数和无人机位置之间的非线性相互作用。为处理这些难题，我们推导了所有机会约束的严格Bernstein型确定性近似，从而得到分布鲁棒重构形式。在此基础上，提出一种交替优化框架，采用逐次凸近似技术对各模块进行凸化处理，高效求解基站波束成形、RIS、STAR-RIS、H-RIS配置及无人机部署子问题。所提算法被证明能单调降低保密中断代价的平滑代理函数，并收敛至鲁棒化问题的稳定点。基于3GPP TR 38.901、TR 36.873和ITU-R P.2109的仿真表明，相较于基准方案，集成UAV-RIS、STAR-RIS和H-RIS能显著降低保密中断概率，并对信道不确定性、遮挡、共谋窃听及硬件损伤展现出强鲁棒性。