广东工业大学学报 ›› 2022, Vol. 39 ›› Issue (06): 53-61.doi: 10.12052/gdutxb.210099

• 综合研究 • 上一篇    下一篇

无人机信息采集系统的端到端吞吐量最大化研究

吴庆捷1, 崔苗1, 张广驰1, 陈伟2   

  1. 1. 广东工业大学 信息工程学院，广东 广州 510006;
    2. 广东省环境地质勘查院，广东 广州 510080
  • 收稿日期:2021-07-06 出版日期:2022-11-10 发布日期:2022-11-25
  • 通信作者: 崔苗(1978-)，女，讲师，博士，主要研究方向为电子信息与无线通信技术，E-mail：cuimiao@gdut.edu.cn
  • 作者简介:吴庆捷(1999-)，男，硕士研究生，主要研究方向为无人机通信
  • 基金资助:
    广东省科技计划项目(2017B090909006，2019B010119001，2020A050515010，2021A0505030015) ；广东特支计划项目(2019TQ05X409)

End-to-End Throughput Maximization for UAV-Enabled Data Collection Systems

Wu Qing-jie1, Cui Miao1, Zhang Guang-chi1, Chen Wei2   

  1. 1. School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China;
    2. Institute of Environmental Geology Exploration of Guangdong Province, Guangzhou 510080, China
  • Received:2021-07-06 Online:2022-11-10 Published:2022-11-25

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摘要： 无人机具有按需快速部署、移动性高、可与地面用户建立起高质量的视距通信链路的优点，能在无线通信和物联网中得到重要的应用。本文研究了一个无人机信息采集系统，在该系统中无人机负责收集多个地面传感器的信息，并将信息回传至信息融合中心。为了最大化信息采集系统的端到端吞吐量，制定了一个联合优化传感器的发射功率、可用带宽的分配、无人机的传输功率和飞行轨迹的优化问题。该优化问题需满足最小信息传输量约束、信息−因果约束、平均和峰值传输功率约束、带宽分配约束和无人机机动性约束，是一个难以直接求解的非凸优化问题。为解决这个问题，本文基于块坐标下降法和连续凸优化方法提出了一个高效的交替优化算法，将问题分解为优化功率带宽和优化无人机飞行轨迹两个子问题，并通过引入松弛变量和一阶泰勒展开的方法将每个子问题变成易于求解的凸优化问题，从而进行交替迭代求解。计算机仿真结果显示所提出的优化算法能够权衡数据收集和数据转发这两段链路，显著提高了系统的端到端吞吐量。同时，通过与另外3种基准方案的性能对比，显示了联合优化功率、带宽和飞行轨迹的必要性。

关键词: 无人机通信, 信息采集, 功率控制, 带宽分配, 飞行轨迹设计

Abstract: Unmanned aerial vehicles (UAVs) have found important applications in wireless communications and internet of things (IoT) due to their advantages of on-demand and swift deployment, high mobility, and high-quality line-of-sight communication links with ground users. In this paper, a UAV-enabled data collection system is studied, where a UAV collects data from multiple sensors and relays the collected data back to a fusion center. In order to maximize the end-to-end throughput of the data collection system, an optimization problem is formulated to jointly optimize the transmit power and bandwidth of the sensors, as well as the transmit power and flight trajectory of the UAV.The optimization problem is subject to the minimum data transmission constraint, the information-causality constraint, the average and peak transmit power constraint, the bandwidth allocation constraint, and the UAV mobility constraint, and this is a non-convex optimization problem which is difficult to solve. To tackle such a difficulty, this paper proposes an efficient alternative optimization algorithm based on the block coordinate descent method and the successive convex optimization method. The algorithm divides the original problem into a transmit power and bandwidth optimization sub-problem; and a UAV trajectory optimization sub-problem.These two sub-problems are both transformed into convex optimization problems by introducing slack variables and applying the first-order Taylor expansion method,then they can be solved iteratively and alternately. Computer simulation results show that the proposed algorithm can strike a balance between the data collection links and the data forwarding links, and can significantly improve the end-to-end throughput of the system, as compared to other three benchmark schemes, which demonstrates the necessity of optimizing power, bandwidth and flight trajectory jointly.

Key words: UAV communication, data collection, power control, bandwidth allocation, trajectory design

中图分类号: 

  • TN929.5
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