Beam Selection Assisted UAV-BS Deployment and Trajectory for Beamspace mmWave Systems

Abstract

Exploiting unmanned aerial vehicles (UAVs) as base stations (UAV-BS) can enhance capacity, coverage, and energy efficiency of wireless communication networks. To fully realize this potential, millimeter wave (mmWave) technology can be exploited with UAV-BS to form mmWave UAV-BS. The major difficulty of mmWave UAV-BS, however, lies in the limited energy of UAV-BS and the multiuser interference (MUI). Beam division multiple access with orthogonal beams can be employed to alleviate the MUI. Since each user has dominant beams around the line of sight direction, beam selection can reduce the power consumption of radio frequency chain. In this paper, we formulate the problem of maximizing the sum rate of all users by optimizing the beam selection for beamspace and UAV-BS deployment in the mmWave UAV-BS system. This nonconvex problem is solved in two steps. First, we propose a signal-to-interference plus noise ratio-based greedy beam selection scheme to ensure that all the ground users in the given area can be served by the UAV-BS, where a zero forcing precoding scheme is used to eliminate the MUI. Then, we utilize the continuous genetic algorithm to find the optimal UAV-BS deployment and beam pattern to maximize the sum rate of all users. Moreover, considering the mobility of the UAV-BS, the UAV-BS trajectory and beam selection for beamspace are optimized in the mmWave UAV-BS system. The simulation results demonstrate the effectiveness of the proposed design for the mmWave UAV-BS system.