期刊
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
卷 71, 期 10, 页码 10910-10922出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2022.3183010
关键词
Autonomous aerial vehicles; Kinematics; Turning; Trajectory optimization; Trajectory planning; Resource management; Wireless networks; Unmanned aerial vehicle; trajectory design; user mobility; UAV kinematic constraints
资金
- National Key R&D Program of China [2020YFB1808100]
- National Natural Science Foundation of China [62001047]
- Young Elite Scientist Sponsorship Program by China Institute of Communications
- Project of China Railway Corporation [P2020G004]
This paper proposes a novel trajectory design for UAV-enabled communications to provide radio coverage to terrestrial mobile users. The paper addresses the optimization problem by considering the kinematic constraints of the UAV and introduces offline and online algorithms to solve the problem. Numerical results demonstrate the effectiveness of these algorithms and show that the online algorithm achieves similar system performance with lower computational complexity.
In this paper, we propose novel three-dimensional (3-D) trajectory designs for unmanned aerial vehicle (UAV)-enabled communications, where a single UAV needs to adaptively determine its locations in a timely manner in order to provide radio coverage to terrestrial mobile users. Taking the kinematic constraints on the speed and the turning angle of the UAV into account, we formulate a UAV trajectory optimization problem to maximize the average throughput of the considered system, while satisfying the coverage requirements of the mobile users simultaneously. To solve this NP-hard problem, we first propose an offline trajectory design algorithm that can determine the whole trajectory of the UAV, assuming that the global information (e.g., channel state information and the users' location information at all time slots) is known a priori. Then, we propose two low-complexity online algorithms that utilize the past and current information of the system only. Numerical results are provided to verify the effectiveness of our proposed algorithms. Moreover, we show that our proposed online algorithms can achieve almost the same system performance as the proposed offline algorithm, while inducing significant lower computational complexity.
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