QoS-aware UAV mounted base station deployment in a disaster scenario with user position estimation

The base station installed on the unmanned aerial vehicle, referred to as the UAV-mounted base station (UBS), is considered an innovative paradigm for restoring cellular connectivity in areas where a terrestrial network does not exist, has been demolished, or is overcrowded. The challenging issue in this context is how to acquire the position information of user equipment (UE), characterize the air-to-ground (A2G) channel, and identify the optimal locations for quality-of-service (QoS)-aware 3D UBS deployment. To tackle these issues, we proposed a framework for 3D UBS deployment with the goal of maximizing the number of UEs covered. First, unlike the existing UBS deployment schemes, which ignore the UEs' localization, we propose a received signal strength indicator (RSSI)-based localization (RBL) approach to localize the randomly distributed UEs. Then, the 3D UBS deployment problem is divided into horizontal position optimization to meet the QoS requirements of individual UEs’ and vertical position optimization for path loss minimization. We propose a K-means initialized grey wolf optimization (KIGWO) approach in which UBSs are deployed to maximize the covered UEs percentage while taking the QoS requirements of individual UEs’ and UBS’ total capacity into account. Finally, the effectiveness of the proposed approach is demonstrated through Monte Carlo simulations conducted in four different environmental scenarios.