论文标题
基于用户当前和预测的位置，在5G蜂窝网络中飞行基站的联合位置和轨迹优化
Joint position and trajectory optimization of flying base station in 5G cellular networks, based on users' current and predicted location
论文作者
论文摘要
如今，无人驾驶汽车（UAV）已得到显着改善，其最重要的应用之一是为蜂窝用户提供临时覆盖范围。由于临时事件，例如地面BS崩溃，恶劣天气条件，自然灾害，变速箱错误等，静态基站无法为所有用户服务，因此配备了小蜂窝BS。无人机基站立即将其发送到目标位置，并建立必要的通信链接，而无需任何预定的基础架构并覆盖该区域。在该区域找到无人机-BS的最佳位置和适当的数字（DB）是一个挑战。因此，在本文中，最佳位置和最佳DBS数量是在用户的当前状态以及由预测确定的后续用户状态下分布的。最后，DBS转换从当前状态到预测的未来位置进行了优化。仿真结果表明，所提出的方法可以在网络上提供可接受的覆盖范围。
Nowadays, Unmanned Aerial Vehicles (UAVs) have been significantly improved, and one of their most important applications is to provide temporary coverage for cellular users. Static Base Station cannot service all users due to temporary crashes because of temporary events such as ground BS breakdowns, bad weather conditions, natural disasters, transmission errors, etc., drones equipped with small cellular BS. The Drone Base Station is immediately sent to the target location and establishes the necessary communication links without requiring any predetermined infrastructure and covers that area. Finding the optimal location and the appropriate number (DBS) of drone-BS in this area is a challenge. Therefore, in this paper, the optimal location and optimal number of DBSs are distributed in the current state of the users and the subsequent user states determined by the prediction. Finally, the DBS transition is optimized from the current state to the predicted future locations. The simulation results show that the proposed method can provide acceptable coverage on the network.
