无人机辅助通感一体化系统中的信息年龄分析优化

于宝泉; 杨炜伟; 王权; 张若愚; 蔡跃明

doi:10.11999/JEIT231175

无人机辅助通感一体化系统中的信息年龄分析优化

doi: 10.11999/JEIT231175

1.
海军航空大学烟台 264001
2.
陆军工程大学南京 210007
3.
中国人民解放军32319部队乌鲁木齐 830002
4.
南京理工大学南京 210094

基金项目: 国家自然科学基金(62171464, 62201266)

详细信息

作者简介:
于宝泉：男，博士，讲师，研究方向为信息年龄、短包通信等

杨炜伟：男，博士，副教授，研究方向为协同通信、认知物联网、隐蔽通信等

王权：男，硕士，助理工程师，研究方向为移动通信、信息通信等

张若愚：男，博士，副教授，研究方向为大规模MIMO、通感一体化技术等

蔡跃明：男，博士，教授，研究方向为移动通信、协同通信、通信安全等

通讯作者:
杨炜伟　wwyang1981@163.com

中图分类号: TN926
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- 被引次数: 46
出版历程
- 收稿日期: 2023-10-30
- 修回日期: 2024-02-23
- 网络出版日期: 2024-03-06
- 刊出日期: 2024-05-30

Age of Information Analysis and Optimization in Unmanned Aerial Vehicles-assisted Integrated Sensing and Communication Systems

1.
Naval Aeronautical University, Yantai 264001, China
2.
Army Engineering University of PLA, Nanjing 210007, China
3.
Unit 32319 of PLA, Urumqi 830002, China
4.
Nanjing University of Science and Technology, Nanjing 210094, China

Funds: The National Natural Science Foundation of China (62171464, 62201266)

摘要

摘要: 在许多监测控制任务中，由于被监测目标和控制中心距离较远，控制中心难以直接获取目标实时的状态信息。无人机(UAV)可以发挥其高移动性优势，减少感知和通信距离，进而提升感知和通信能力，为远距离目标状态信息实时获取问题提供了新思路。对此，该文研究了UAV辅助通感一体化系统中的信息年龄(AoI)分析优化问题，首先分析了控制中心的状态更新过程，然后推导出平均峰值AoI的闭式表达式。进一步地，在多UAV多目标场景中，通过优化UAV在空中的感知位置和通信位置以及UAV和目标的匹配关系，来进一步降低系统的平均峰值AoI，改善状态更新的实时性。仿真结果验证了理论分析的正确性，同时表明了相比于对比方法，所提优化方法可以有效改善系统的AoI性能。
- 信息年龄 /
- 无人机辅助系统 /
- 通感一体化
Abstract: In many monitoring and control tasks, it is difficult for the control center to get the real-time status information directly because of the distance between the monitored target and the control center. The Unmanned Aerial Vehicles (UAV) can make full use of its advantages of high mobility, reduce the sensing and communication distance, and then improve the sensing and communication capabilities, which provides a new idea for real-time acquisition of remote target status information. In this paper, the optimization problem of Age of Information (AoI) analysis in UAV-assisted integrated sensing and communication system is studied. Firstly, the status update process of control center is analyzed, and then the closed-form expression of average peak AoI is derived. Further, in the multi-UAV multi-target scenario, the average peak AoI of the system is further reduced by optimizing the perception position and communication position of the UAV in the air, as well as the matching relationship between the UAV and the target, and the real-time status update is improved. The simulation results verify the correctness of the theoretical analysis, and show that the proposed optimization method can effectively improve the AoI performance of the system compared with the benchmark methods.
- Age of Information (AoI) /
- Unmanned Aerial Vehicles (UAV)-assisted system /
- Integrated sensing and communication

HTML全文

图 1 系统模型

下载: 全尺寸图片幻灯片

图 2 AoI更新过程

下载: 全尺寸图片幻灯片

图 3 平均峰值AoI随UAV高度变化图

下载: 全尺寸图片幻灯片

图 4 单UAV单目标下3种不同优化方法性能对比图

下载: 全尺寸图片幻灯片

图 5 多UAV多目标下两种不同优化方法性能对比图

下载: 全尺寸图片幻灯片

图 6 多UAV多目标下不同任务平均峰值AoI性能图

下载: 全尺寸图片幻灯片

1 AoI性能优化算法

初始化： ${x_{\text{c}}}\left( 0 \right)$ , ${x_{\text{s}}}\left( 0 \right)$ , ${\boldsymbol{Q}}$ 。
For $m = 1:M$
For $k = 1:K$
$t = 0$
Do
对于 $x_{\text{c}}^m \in \left[ {\min \left\{ {x_{\text{s}}^m\left( t \right),{x_1}} \right\},\min \left\{ {x_{\text{s}}^m\left( t \right),{x_2}} \right\}} \right]$ ，采用　　　　黄金分割法得到优化后的 $x_{\text{c}}^m\left( {t + 1} \right)$ 。
对于 $x_{\text{s}}^m \in \left[ {x_{\text{c}}^m\left( {t + 1} \right),X} \right]$ ，采用黄金分割法得到最佳的　　　　 $x_{\text{s}}^m\left( {t + 1} \right)$ 。
$t \leftarrow t + 1$ 。
Until $t > {t_{\max }}$
根据优化后的 $x_{\text{c}}^m$ 和 $x_{\text{s}}^m$ ，计算得到最小的平均峰值AoI $\bar \varDelta {_k^{m*}}$ 。
If $\bar \varDelta {_k^{m*}} \le \tau$
$Q_k^m \leftarrow \bar \varDelta _{k^{m*}}$ 。
Else
$Q_k^m \leftarrow \infty$ 。
End If
End for
End for
采用匈牙利算法优化UAV与被监测目标的匹配关系，得到 ${{\boldsymbol{Q}}^*}$ 。

下载: 导出CSV

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