It is widely accepted that integrating intelligent reflecting surfaces (IRSs) with unmanned aerial vehicles (UAV) or drones can assist wireless networks in improving network coverage and end user Quality of Service (QoS). However, the critical constrain of drones is their very limited hovering/flying time. In this paper we propose the concept of robotic aerial IRSs (RA-IRSs), which are in essence drones that in addition to IRS embed an anchoring mechanism that allows them to grasp in an energy neutral manner at tall urban landforms such as lampposts. By doing so, RA-IRSs can completely eliminate the flying/hovering energy consumption and can offer service for multiple hours or even days (something not possible with UAV-mounted IRSs). Using that property we show how RA-IRS can increase network performance by changing their anchoring location to follow the spatio-temporal traffic demand. The proposed methodology, developed through Integer Linear Programming (ILP) formulations offers a significant Signal-to-Noise (SNR) gain in highly heterogeneous regions in terms of traffic demand compared to fixed IRS; hence, addressing urban coverage discrepancies effectively. Numerical simulations validate the superiority of RA-IRSs over fixed terrestrial IRSs in terms of traffic serviceability, sustaining more than 2 times the traffic demand in areas experiencing high heterogeneity, emphasizing their adaptability in improving coverage and QoS in complex urban terrains.

翻译：普遍认为，将智能反射面与无人机或飞艇集成可辅助无线网络提升覆盖范围和终端用户服务质量。然而，无人机关键局限在于极短的悬停/飞行时间。本文提出机器人空中智能反射面（RA-IRS）概念，其本质是嵌入锚定机制的无人机，可在能量中性状态下吸附于路灯杆等城市高层地物。通过此方式，RA-IRS能完全消除飞行/悬停能耗，实现数小时甚至数天的持续服务（这是无人机载IRS无法实现的）。利用该特性，我们展示RA-IRS如何通过改变锚定位置来跟随时空流量需求增强网络性能。基于整数线性规划公式提出的方法，在流量需求高度异构区域相比固定IRS实现了显著的信噪比增益，从而有效解决城市覆盖不均问题。数值仿真验证了RA-IRS在流量服务能力上超越固定地面IRS，在高异构区域可承载超过2倍流量需求，凸显其在复杂城市地形中改善覆盖和服务质量的适应性。