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无人机部署位置和信道分配联合优化方法
引用本文:解其乐,赵文栋,俞星月,刘存涛.无人机部署位置和信道分配联合优化方法[J].解放军理工大学学报,2023(5):44-51.
作者姓名:解其乐  赵文栋  俞星月  刘存涛
作者单位:陆军工程大学 通信工程学院,江苏 南京 210007
基金项目:国家自然科学基金(61671471)
摘    要:无人机在执行周期性数据采集任务时,由于任务执行时间有限、无线传感器的部署位置和功能不同,会存在无法采集全部数据、所采集数据具有不同应用价值等问题。基于此,提出了一种综合考虑采集公平性和重要度的数据采集评价方法。以采集周期内无人机采集数据的加权数据量最大化为优化目标,对无人机的悬停位置和信道分配进行联合优化。将该联合优化问题建模为一个非线性混合整数规划问题,并提出一种鲸鱼优化资源分配算法(whale optimized resource allocation algorithm, WORAA)对问题进行求解。仿真结果表明,相较于传统方法,在重要度影响不大的条件下,采集数据公平性有比较明显的提升,在满足公平性要求的基础上,加权数据量更大。

关 键 词:无人机  数据采集  公平性  无线传感器
收稿时间:2023/2/14 0:00:00

Joint Optimization of UAV Deployment Position and Channel Allocation
XIE Qile,ZHAO Wendong,YU Xingyue,LIU Cuntao.Joint Optimization of UAV Deployment Position and Channel Allocation[J].Journal of PLA University of Science and Technology(Natural Science Edition),2023(5):44-51.
Authors:XIE Qile  ZHAO Wendong  YU Xingyue  LIU Cuntao
Abstract:Due to the limited execution time, different mounted positions and functions of wireless sensors, the UAV may not be able to collect all the data, and the collected data may have different application values when the UAV is used to carry out the task of periodic data collection. Therefore, a data collection evaluation method is proposed to comprehensively consider the fairness and importance of acquisition. Based on the optimization objective of maximizing the weighted data volume of the UAV collected within the acquisition period, the hovering position and channel allocation of the UAV are jointly optimized. The joint optimization problem is modeled as a nonlinear mixed integer programming problem, and a whale optimization resource allocation algorithm (WORAA) is proposed to solve the problem. The simulation results show that compared with the traditional methods, this method significantly improves the fairness of data collection under the condition that the importance degree has little influence; on the basis of meeting the fairness requirement of the collected data, the weighted data volume is higher.
Keywords:
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