基于IRS辅助通信的无线供能传感器网络信息年龄优化

doi:10.19678/j.issn.1000-3428.0066149

摘要/Abstract

摘要：

无线传感器与基站之间容易因障碍物阻挡，影响信息交付的及时性，传感器能量供应不足也会引起信息年龄(AoI)性能下降。构建一种基于智能反射面(IRS)辅助通信的无线供能传感器网络系统模型，提出一个联合优化能量发射矩阵、IRS相移和传感器调度的多变量系统总信息年龄最小化优化问题。由于调度变量的二进制性质和IRS相移约束的非凸性质，导致该优化问题无法被直接求解，因此利用变量松弛和半正定凸松弛方法将原非凸问题转化为凸问题，并设计一种基于半正定凸松弛的信息年龄调度优化算法。实验结果表明，当能量站最大发射功率为45 dBm及IRS反射单元数为30时，所提算法相比循环调度算法、非能量收集算法，能将系统总AoI最大分别降低38%、46%，不仅可以为无线传感器持续供能，而且能提高系统的AoI性能。

关键词: 信息年龄, 无线供能传感器网络, 能量收集, 智能反射面, 传感器调度

Abstract:

To solve the problems that information freshness is easily affected by obstacles between the wireless sensor and Base Station(BS) and that insufficient energy supply of the sensor will lead to degradation of the Age of Information (AoI) performance, a wireless powered sensor network system model based on Intelligent Reflecting Surface(IRS)-assisted communication is proposed.First, an optimization problem of minimizing the sum AoI of multivariable systems is established by jointly optimizing energy emission matrix, IRS phase-shift, and sensor scheduling.Second, because of the binary characteristic of scheduling variables and the nonconvexity of IRS phase-shift constraints, the optimization problem cannot be solved directly.Thus, the original non-convex problem is transformed into a convex problem using variable relaxation and semi-definite convex relaxation, and an AoI scheduling optimization algorithm based on semi-definite convex relaxation is proposed.The experimental results show that when the maximum transmission power of the energy station is 45 dBm and the number of IRS reflection units is 30, the proposed algorithm can reduce the total AoI of the system by a maximum of 38% and 46% compared to the cycle scheduling and non-energy harvesting algorithms, respectively. It can not only continuously power wireless sensors but also improve the AoI performance of the system.

Key words: Age of Information(AoI), wireless powered sensor network, Energy Harvesting(EH), Intelligent Reflecting Surface(IRS), sensor scheduling

杨荐焜, 王茜竹, 冉泳屹, 陈丰. 基于IRS辅助通信的无线供能传感器网络信息年龄优化[J]. 计算机工程, 2023, 49(8): 146-153,162.

Jiankun YANG, Qianzhu WANG, Yongyi RAN, Feng CHEN. Age of Information Optimization for Wireless Powered Sensor Network Based on IRS-assisted Communication[J]. Computer Engineering, 2023, 49(8): 146-153,162.

https://www.ecice06.com/CN/Y2023/V49/I8/146

图/表 8

图1 基于IRS辅助通信的无线供能传感器网络

Fig.1 Wireless powered sensor network based on IRS assisted communication

表1 仿真参数设置

Table 1 Simulation parameters setting

参数	符号	取值
噪声功率/dBm	$ {\sigma }^{2} $	-80
能量站位置	$ {L}_{\mathrm{P}\mathrm{S}} $	(-5, 0)
基站位置	$ {L}_{\mathrm{B}\mathrm{S}} $	(80, 0)
IRS位置	$ {L}_{\mathrm{I}\mathrm{R}\mathrm{S}} $	(4, 4)
无线传感器位置	$ {L}_{\mathrm{S}\mathrm{N}}\left(k\right) $	随机分布在圆心为(1, 0)半径为2 m的圆内
能量站到无线传感器路径损耗系数	$ {\varphi }_{\mathrm{P}\mathrm{S}} $	2
无线传感器到IRS路径损耗系数	$ {\varphi }_{\mathrm{S}\mathrm{I}} $	3.3
IRS到BS路径损耗系数	$ {\varphi }_{\mathrm{I}\mathrm{B}} $	3.3
数据包到达概率	$ \lambda $	0.5
能量转换效率	$ \chi $	0.8

图2 不同算法的性能对比

Fig.2 Performance evaluation of different algorithms

图3 能量站最大发射功率对系统总AoI的影响

Fig.3 Effect of maximum emission power of energy stations on the total AoI of system

图4 IRS反射单元数对系统总AoI的影响

Fig.4 Effect of the number of IRS reflection units on the total AoI of systems

图5 能量收集阈值和IRS反射单元数对系统总AoI的影响

Fig.5 Effect of energy harvesting threshold and IRS reflection units on the total AoI of system

图6 SNR阈值和传感器个数对系统总AoI的影响

Fig.6 Effect of the SNR threshold and the number of sensor on the total AoI of system

图7 不同算法下IRS反射单元数对系统总AoI的影响

Fig.7 Effect of the number of IRS reflection units on the total AoI of system under different algorithms

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