In this paper, we propose a novel wireless architecture, mounted on a high-altitude aerial platform, which is enabled by reconfigurable intelligent surface (RIS). By installing RIS on the aerial platform, rich line-of-sight and full-area coverage can be achieved, thereby, overcoming the limitations of the conventional terrestrial RIS. We consider a scenario where a sudden increase in traffic in an urban area triggers authorities to rapidly deploy unmanned-aerial vehicle base stations (UAV-BSs) to serve the ground users. In this scenario, since the direct backhaul link from the ground source can be blocked due to several obstacles from the urban area, we propose reflecting the backhaul signal using aerial-RIS so that it successfully reaches the UAV-BSs. We jointly optimize the placement and array-partition strategies of aerial-RIS and the phases of RIS elements, which leads to an increase in energy-efficiency of every UAV-BS. We show that the complexity of our algorithm can be bounded by the quadratic order, thus implying high computational efficiency. We verify the performance of the proposed algorithm via extensive numerical evaluations and show that our method achieves an outstanding performance in terms of energy-efficiency compared to benchmark schemes.
翻译:在本文中,我们提出一个新的无线结构,它安装在高空航空平台上,由可重新配置的智能表面(RIS)促成。通过在航空平台上安装RIS,可以实现丰富的光线和全域覆盖,从而克服常规地面光线和广域覆盖的局限性。我们考虑一个假设方案,即城市地区交通的突然增加促使当局迅速部署无人驾驶航空车辆基地站(UAV-BS),为地面用户服务。在这种情况下,由于来自地面的直接回航链路可能因来自城市地区的若干障碍而受阻。我们提议利用航空光线和光谱仪反映背航信号,以便成功到达UAV-BS。我们共同优化航空光线和光谱部分的定位和阵列战略,从而导致每个UAV-BS基站(UA-BS)的能源效率的提高。我们表明,我们的算法的复杂性可以受二次测序的束缚,从而意味着高计算效率。我们通过广泛的数字评估来核查拟议算法的绩效,以先进的方法实现出色的基准。