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

Zuo, X., Zhang, J., Chenery-Morris, S. and Mu, X., 2021. Beam Selection Assisted UAV-BS Deployment and Trajectory for Beamspace MmWave Systems. Wireless Communications and Mobile Computing, 2021, 1363586.

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DOI: 10.1155/2021/1363586


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 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 zeroforcing 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 UAVBS, 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.

Item Type:Article
Uncontrolled Keywords:Unmanned aerial vehicle; interference mitigation; beamspace; beam selection; deployment optimization; multiuser; trajectory optimization
Group:Faculty of Science & Technology
ID Code:36047
Deposited By: Symplectic RT2
Deposited On:24 Sep 2021 15:23
Last Modified:14 Mar 2022 14:29


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