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基于MPC的无人机辅助通信在线控制策略*

王逸飞1,2,3, 黄伟1,2,3, 向俊彦1,2,3, 贺晓赫1,2,3, 梁旭文1,3,†   

  1. 1 中国科学院微小卫星创新研究院,上海 201203;
    2 上海科技大学信息科学与技术学院,上海 201210;
    3 中国科学院大学,北京 100049
  • 收稿日期:2023-04-27 修回日期:2023-10-09 发布日期:2023-11-03
  • 通讯作者: † E-mail: 18217631362@163.com
  • 基金资助:
    *中国科学院青年创新促进会(2019293)资助

UAV-assisted communication online control strategy based on MPC

WANG Yifei1,2,3, HUANG Wei1,2,3, XIANG Junyan1,2,3, He Xiaohe1,2,3, LIANG Xuwen1,3,†   

  1. 1 Innovation Academy for Microsatellites of CAS, Shanghai 201203, China;
    2 School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China;
    3 University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2023-04-27 Revised:2023-10-09 Published:2023-11-03

摘要: 本文针对无人机通信网络中多用户间干扰大、动力学模型复杂度高,以及设计实时最优控制策略难等问题展开研究。首次在四旋翼无人机通信网络中引入多天线技术,提出了3D MU-MISO场景下的复杂通信网络模型,该模型考虑了无人机姿态角的小尺度变化对信道质量的影响,并且采用空分多址接入技术有效避免用户间干扰。针对上述场景,基于MPC算法设计了一种在线的无人机姿态控制与资源分配策略。通过滚动式在线求解有限时间窗长的开环控制问题,实现最大化无人机通信系统的平均频谱效率。仿真结果表明,所提出的耦合通信模型能够带来显著系统增益,同时控制策略可以有效实现动态环境下无人机飞行轨迹的在线优化和通信资源的在线分配。

关键词: 无人机通信, 轨迹优化, 姿态控制, 资源分配, 在线控制策略

Abstract: This paper addresses the research challenges in unmanned aerial vehicle communication networks, including significant interference among multiple users, high complexity of dynamic models, and the difficulty in designing real-time optimal control strategies. For the first time, the multi-antenna technology is introduced into the quadcopter UAV communication network, proposing a complex communication network model under the 3D MU-MISO scenario. This model takes into account the small-scale variations of UAV attitudes and their impact on channel quality. Additionally, the SDMA technology is employed to effectively mitigate interference among users. In this context, an online UAV attitude control and resource allocation strategy based on MPC algorithm is designed. By iteratively solving the open-loop control problem with a rolling window of limited time duration, achieving the maximization of the average spectral efficiency of the UAV communication system. Simulation results demonstrate that the proposed coupled communication model significantly improves system gains, and the control strategy efficiently optimizes UAV flight trajectories and allocates communication resources in dynamic environments.

Key words: UAV communication, trajectory optimization, attitude control, resource allocation, online control strategy

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