In recent years with the increasing use of unmanned aerial vehicles, UAV-based stations are widely used for establishing fast and cost-effective communications, considering the high cost and time-consuming nature of building ground-based stations. The study examines how air base stations or access points are used in cases of increased network demand and covering holes in existing ground infrastructure to provide wireless services to users to improve network performance in urban environments. Thus, the three design goals are the minimum number of UAVs, optimal position of deployment and Optimal allocation of UAV transmission power are investigated. To these goals, a method of particle swarm optimization based on signal-to-noise ratio plus interference (SINR) has been proposed. Also, by exploiting the shape of the optimal power allocation package and the resulting SINR, the proposed PSO-based method optimizes the acquisition of the UAV location generation by generation. Furthermore, a K-means clustering initial method has been presented to improve the performance of the proposed particle swarm optimization algorithm compared to the initialization algorithm and power reduction method to further reduce the total transmission power. The simulation results show that with the optimal UAVs height, improvement of 38% will be achieved by signal-to-interference plus noise ratio received by users.