The use of Unmanned Aerial Vehicles (UAVs) as mobile Base Stations (BSs) in wireless communication is
emerging as an effective technique that should be used for the services planned in the next-generation cellular
networks or in disaster situations. Currently, effective 3D placement of BS mounted on UAVs or Drones
(Drone-BS), also called Low-altitude Air Platforms, in the defined area significantly increases the Quality
of Service (QoS) of wireless communication. This study has been aimed to be performed dynamic
deployments (location optimization) of Drone-BSs randomly distributed in the 3D plane in order to optimally
cover the users in the urban environment according to the Air-to-Ground (ATG) model. Using new
approaches based on the Electromagnetism-Like (EML) Algorithm and the Whale Optimization Algorithm
(WOA), which are widely used in the literature and are meta-heuristic, it was planned to be covered the
maximum number of users on the ground by multiple Drone-BSs. In addition, Extensive-interval Optimal
Fitness Search Algorithm (EOFSA-EML) and Discrete-interval Optimal Fitness Search Algorithm (DOFSAEML) approaches were developed based on the EML algorithm. Based on comparison metrics for multiple
Drone-BSs distributed by EOFSA-EML, DOFSA-EML, and Pure-WOA, it has been found that EML-based
algorithms achieve optimal results compared to Pure-WOA.
