Unmanned Aerial Vehicle Base Station (UAV-BS) Deployment With Millimeter-Wave Beamforming

• Published in: IEEE internet of things journal Vol. 7; no. 2; pp. 1336 - 1349
• Main Authors: Xiao, Zhenyu, Dong, Hang, Bai, Lin, Wu, Dapeng Oliver, Xia, Xiang-Gen
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.02.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Achievable sum rate; Algorithms; Antennas; Array signal processing; artificial bee colony (ABC) algorithm; Beamforming; Computer simulation; Data collection; deployment; Global optimization; Internet of Things; Millimeter wave communication; Millimeter waves; millimeter-wave (mmWave) communications; Optimization; Steering; Swarm intelligence; unmanned aerial vehicle (UAV) communications; Unmanned aerial vehicles; Wireless communication; Wireless communications
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2019.2954620

Unmanned aerial vehicle (UAV) with flexible mobility and low cost has been a promising technology for wireless communication. Thus, it can be used for wireless data collection in Internet of Things (IoT). In this article, we consider millimeter-wave (mmWave) communication on a UAV platform, where the UAV base station (UAV-BS) serves multiple ground users, which generate big sensor data. Both the deployment of the UAV-BS and the beamforming design have essential impact on the throughput of the system. Thus, we formulate a problem to maximize the achievable sum rate of all the users, subject to a minimum rate constraint for each user, a position constraint of the UAV-BS, and a constant-modulus (CM) constraint for the beamforming vector. We solve the nonconvex problem with two steps. First, by introducing the approximate beam pattern, we solve the deployment and beam gain allocation subproblem. Then, we utilize the artificial bee colony (ABC) algorithm to solve the beamforming subproblem. For the global optimization problem, we find the near-optimal position of the UAV-BS and the beamforming vector to steer toward each user, subject to an analog beamforming structure. The simulation results demonstrate that the proposed solution can achieve a more superior performance than the present random steering beamforming strategy in terms of achievable sum rate.