智能反射面部署用于低空覆盖：照明几何、方向特性与优化
Intelligent Reflecting Surface Deployment for Low-Altitude Coverage: Illumination Geometry, Directional Characteristics, and Optimization
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中文总结 AI 辅助
针对低空覆盖，本文建立含IRS辐射方向图的三维信道模型，构建预算约束下的IRS部署优化问题，提出混合整数AO算法，仿真显示其比基准方案的最坏情况SNR更高。
中文摘要 AI 辅助
地面基站（BS）通常配置固定下倾角以服务地面用户，即便在视距（LoS）传播条件下，也会导致低空空域的照明较弱。本文在保留现有基站配置的同时，建立了包含基站和智能反射面（IRS）辐射方向图的三维（3D）低空覆盖信道模型。我们构建了预算约束下的IRS部署问题，该问题需联合确定候选站点选择、IRS方向及相位偏移，以最大化三维低空空域内的最坏情况信噪比（SNR）。所选站点及优化后的IRS参数在部署后保持固定，形成准静态IRS配置。我们通过推导满足基站主瓣条件的非负安装高度范围，表征了固定下倾角基站与屋顶候选点之间的照明几何。映射后的主瓣高度边界间距随基站与站点的水平距离线性增长，且随基站天线数量的增加呈反比减小。我们进一步推导了区域最坏情况归一化阵列增益的解析下界，该增益可通过IRS相位设计在具有不同方向跨度的服务方向上实现。当维持相同的最坏情况归一化增益保证时，所需的足够方向跨度随IRS单元数量的平方根呈反比减小。我们提出了一种混合整数交替优化（AO）算法来求解该问题。仿真结果验证了这些解析表征，并表明所提方案在不同部署预算下均比基准方案实现了更高的最坏情况信噪比。
英文摘要
Terrestrial base stations (BSs) are typically configured with fixed downtilt to serve ground users, resulting in weak illumination of low-altitude airspace even under line-of-sight (LoS) propagation. In this paper, we establish a channel model that incorporates BS and intelligent reflecting surface (IRS) radiation patterns for three-dimensional (3D) low-altitude coverage while preserving the existing BS configuration. We formulate a budget-constrained IRS deployment problem that jointly determines candidate-site selection, IRS orientations, and phase shifts to maximize the worst-case signal-to-noise ratio (SNR) over the 3D low-altitude airspace. The selected sites and optimized IRS parameters remain fixed after deployment, yielding a quasi-static IRS configuration. We characterize the illumination geometry between the fixed-downtilt BS and rooftop candidates by deriving the nonnegative installation-height range satisfying the BS main-lobe condition. The separation between the mapped main-lobe height boundaries grows linearly with horizontal BS-to-site distance and decreases inversely with the number of BS antennas. We further derive an analytical lower bound on the regional worst-case normalized array gain achievable through IRS phase design over served directions with different direction spans. The resulting sufficient direction span decreases inversely with the square root of the number of IRS elements when the same worst-case normalized gain guarantee is maintained. We develop a mixed-integer alternating optimization (AO) algorithm to solve the resulting problem. Simulation results validate the analytical characterizations and show that the proposed scheme achieves higher worst-case SNR than benchmarks across different deployment budgets.
发表机构
- Tsinghua University（清华大学）
机构由 AI 辅助整理，请以论文原文为准。
