Performance analysis of beamforming for high altitude platform systems

High Altitude Platform Systems (HAPS) are communication systems composed of platforms such as unmanned aerial vehicles, balloons, or aircraft, typically positioned in the stratosphere at an altitude of around 20 km. These platforms provide communication, observation, and data collection services over a wide geographical area. HAP systems generally operate in a fixed position over a specific region, delivering high-quality broadband communication services to the target area. In this thesis, the aim is to deploy HAPS in strategic and densely populated regions. During the deployment process, factors such as coverage requirements and user demands were considered. Using the Non-dominated Sorting Genetic Algorithm II (NSGA-II), the HAPS locations that maximize coverage in the target area and best meet the user demands in densely populated regions were determined. In a HAP system that has been positioned, it is aimed to divide users into groups and provide services to users using the appropriate beam generation and orientation technique. In order to cluster users, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and K-Means algorithms were employed, while the NSGA-II and Multi-Objective Particle Swarm Optimization (MOPSO) algorithms were utilized to meet user demands and minimize the power consumption of the HAP system for service provision.