Improved Marine Predators Algorithm for Energy Efficient Placement of UAV-BSs

Drones operating as flying base stations, or UAV-BSs, are receiving a lot of interest as an appropriate strategy for mobile communication, especially for emergencies. When terrestrial base stations malfunction or there are unexpected increases in demand, UAVs can be quickly deployed to provide continuous service. To improve downlink coverage efficiency and minimize energy consumption, this research discusses the state of positioning UAV-BSs optimally and taking into account both user distribution and drone altitude. An improved version of the Marine Predators Algorithm (MPA) is introduced to solve this NP-hard issue that integrates elements from the original MPA, incorporating the concept of chaotic maps and the Opposition-Based Learning (OBL) mechanism. In several scenarios, our results show that, compared to the original MPA, the Whale optimization algorithm (WOA), and the Grey Wolf optimization (GWO) algorithms, the improved MPA is a reliable and effective method for placing UAVs in static situations.