Seraph: a stochastic operational approach for the deployment of multi-antenna UAV-assisted networks

Recently, UAV-mounted mobile base stations (UAVs-MBS) have gained significant attention as an effective solution for providing essential wireless communication services and connectivity to ground users (GUs) in various environments. Smart antenna technologies are vital for both current and next-generation communication networks, particularly in 5 G and beyond. However, implementing smart antenna-assisted UAVs-MBS networks presents a complex multi-objective optimization problem, and traditional techniques often fall short in efficiency and inclusivity. In this study, we propose a viable hybrid method to tackle the challenge of minimizing the number of smart antenna-enabled UAVs-MBS required to achieve higher Line-of-Sight probabilities and coverage levels, while also determining the optimal 3D coordinates for a group of dispersed GUs. Our approach utilizes a low-complexity multi-objective algorithm called SERAPH, which incorporates a novel two-stage hybrid evolutionary algorithm alongside a multi-criteria decision-making method. Additionally, SERAPH features 3D multi-beamforming and coordination mechanisms to enhance wireless coverage and effectively extend the system’s lifespan. We validate the effectiveness of SERAPH through comprehensive comparative analyses with various state-of-the-art algorithms. Our results demonstrate that the proposed method significantly outperforms existing approaches in terms of accuracy and efficiency.