Joint User Association and UAV Placement in HAP-UAV Integrated Networks

In this thesis, a collaboration scheme between a high-altitude platform (HAP) and several unmanned aerial vehicles (UAVs) for wireless communication networks is investigated. The HAP is the centralized entity configuring and managing the network and allocating the bandwidth ratios to users, while the UAVs function as relays to increase coverage and provide better service to ground users. The main objective of this study is to maximize the total downlink throughput of the ground users by optimizing the UAVs' three-dimensional (3D) placements and user associations. An optimization problem is formulated and a separate genetic algorithm-based approach combined with the exhaustive search algorithm is proposed to solve the optimization problem. The K-means algorithm is also utilized to find the initial UAV placement to reduce the convergence time of the proposed genetic algorithm-based allocation that jointly optimizes user association and 3D UAV position. The performance of the proposed algorithm is analyzed in terms of convergence time, complexity, and fairness. Finally, the simulation results show that the proposed HAP-UAV integrated network achieves a higher total throughput through joint user association and UAV placement schemes compared to a scheme with one HAP serving all users.