AI 中文总结
本文针对无人机搭载IRS辅助的FSO系统，基于惠更斯-菲涅耳原理推导了统计信道模型，经MC仿真验证后，为最小化中断概率提供了IRS最优放置的设计准则。
AI 中文摘要
将光学智能反射面（IRS）集成到无人机（UAV）等空中平台，已被提出用于缓解自由空间光（FSO）系统的视距（LoS）约束、扩展覆盖范围并提升部署灵活性。然而，无人机悬停时在位置和姿态上产生的失准误差可能会降低连通性并损害端到端信道质量。本文基于惠更斯-菲涅耳原理，推导了入射到光学IRS以及由其反射的电场的新表达式，所得表达式适用于任意入射和反射传播方向的组合。基于该框架，我们推导了一个闭式统计信道模型，该模型可捕获存在随机无人机波动时，由无人机搭载IRS辅助的FSO链路的几何损耗和失准损耗。特别地，假设无人机位置和姿态均服从高斯波动，我们建立了接收透镜处的波束失准统计模型。所提出的解析模型通过蒙特卡洛（MC）仿真得到验证，并进一步用于提供关于无人机搭载IRS最优放置的实用设计准则，以最小化中断概率。
英文摘要
Integrating optical intelligent reflecting surfaces (IRSs) into aerial platforms, such as unmanned aerial vehicles (UAVs), has been proposed to relax the line-of-sight (LoS) constraint, extend coverage, and enhance deployment flexibility of free space optical (FSO) systems. However, misalignment errors induced by the UAV hovering, in both position and orientation, may degrade connectivity and impair the end-to-end channel quality. In this paper, we develop novel expressions for the electric fields incident on and reflected by an optical IRS, based on the Huygens-Fresnel principle. The resulting expressions are applicable for any combination of incident and reflected propagation directions. Building on this framework, we derive a closed-form statistical channel model that captures the geometric and misalignment losses of an FSO link assisted by a UAV-mounted IRS in the presence of random UAV fluctuations. In particular, we develop a statistical model for the beam misalignment at the receiver lens, assuming Gaussian fluctuations in both the UAV position and orientation. The proposed analytical model is validated through Monte Carlo (MC) simulations and is further used to provide practical design guidelines regarding the optimal placement of the UAV-mounted IRS for the minimization of the outage probability.
Comments13 pages, 3 figures, conference
