Optimization applications for HAPS networks

The indispensable importance of communication in human life is increasing with each passing day. This situation encourages the development of new technologies in the field of communication. One of the commonly used technologies in wireless communication is terrestrial networks (TN). However, in the modern world, changing living conditions, particularly in regions far from city centers, highlight the inadequacies of TN technology and lead to the growing importance of non-terrestrial networks (NTN). NTN refers to a communication infrastructure that provides connectivity using space-based communication networks beyond terrestrial boundaries. These networks play a critical role in providing global coverage and offering services in regions where infrastructure is limited or nonexistent. Among NTN technologies, high altitude platform stations (HAPS) are gaining increasing attention in the field of wireless communication due to their advantages. Compared to TNs, HAPS offers numerous benefits, making it a more efficient and effective solution. However, this technology is still in the development stage and has not yet reached the desired level. To achieve the targeted performance levels of HAPS systems, various optimization algorithms are utilized. At this point, significant efforts are being made to enhance battery life, improve resilience to weather conditions, and optimize communication systems. In the context of improving communication quality, objectives such as serving more users, increasing data transmission rates, and enhancing system performance are prioritized. In this thesis, the sum-rate parameter, a key performance indicator in wireless communication within HAPS systems, was optimized using particle swarm optimization (PSO), artificial bee colony optimization (ABC), and gray wolf optimization (GWO) algorithms. For the GWO algorithm, optimization results were compared under various scenarios, including different weather conditions, varying numbers of base stations, indoor and outdoor user conditions, and different operating frequencies.