Optimal precoding and deployment of millimeter-wave drone base station

Drones are cost effective devices and can be easily deployed at various locations even places that aren't covered by the terrestrial networks. It is evaluated that wireless telecommunication sector can be one of the promising areas for the use of drones. Flexible deployment option give rise to better line-of-sight channel conditions and this makes drone base stations a promising technology for the telecommunication sector. Especially recent developments in millimeter-wave Massive MIMO transmission and beamforming techniques help drone base station become feasible, provide broadband data rates and enable simultaneous transmission to multiple ground users. In this work we consider the problem of fair deployment (i.e. positioning) of drone base stations and analog MIMO beamforming that maximizes SINR and compare K-Means clustering and Particle Swarm Optimization methods with respect to proportional fair data rates. Simulation results reveal that careful K-Means clustering of ground users, together with DFT-based beamforming provides a promising performance.