Unmanned Aerial Vehicles (UAVs) are increasingly used as cost-effective and flexible Wi-Fi Access Points (APs) and cellular Base Stations (BSs) to enhance Quality of Service (QoS). In disaster management scenarios, UAV-based networks provide on-demand wireless connectivity when traditional infrastructures fail. In obstacle-rich environments like urban areas, reliable high-capacity communications links depend on Line-of-Sight (LoS) availability, especially at higher frequencies. Positioning UAVs to consider obstacles and enable LoS communications represents a promising solution that requires further exploration and development. The main contribution of this paper is the Traffic- and Obstacle-aware UAV Positioning Algorithm (TOPA). TOPA takes into account the users' traffic demand and the need for LoS between the UAV and the ground users in the presence of obstacles. The network performance achieved when using TOPA was evaluated through ns-3 simulations. The results show up to 100% improvement in the aggregate throughput without compromising fairness.

翻译：无人机（UAV）正越来越多地被用作经济高效的灵活Wi-Fi接入点（AP）和蜂窝基站（BS），以提升服务质量（QoS）。在灾害管理场景中，基于无人机的网络能够在传统基础设施失效时提供按需无线连接。在诸如城市等障碍物密集的环境中，可靠的高容量通信链路依赖于视距（LoS）可用性，尤其是在较高频率下。考虑障碍物并实现视距通信的无人机定位，是一种需要进一步探索和开发的有前景的解决方案。本文的主要贡献在于提出了流量与障碍物感知的无人机定位算法（TOPA）。TOPA综合考虑了用户的流量需求以及在存在障碍物的情况下无人机与地面用户之间实现视距通信的需求。通过ns-3仿真评估了使用TOPA时的网络性能。结果表明，在不影响公平性的前提下，总吞吐量提升了高达100%。