IRS辅助供能的多用户MEC系统性能研究

Research on Performance of Multi-user MEC System with IRS-assisted Energy Supply

在物联网(IoT)场景中,边缘服务器可有效缓解IoT设备计算能力有限的问题,如何保证IoT设备的能量供应成为研究热点之一.无线能量传输(WPT)与移动边缘计算(MEC)的组合是一种解决方案,但混合接入点(HAP)与IoT设备之间不能保证总是存在直连链路.为了处理这个问题,考虑利用智能反射表面(IRS)辅助无线能量传输与任务卸载.在多用户MEC系统下,当IoT设备采用二进制卸载时,联合能量传输时间优化、卸载决策以及调度顺序以求得最小系统处理时延问题是一个混合整数非凸问题.考虑HAP与IoT设备之间的信道差异,采用一种两层交替迭代的算法,并利用MEC的计算能力最小化系统处理时延.实验结果表明,所用方法收敛快,能有效缩短系统处理时延,在IRS的辅助下能明显提升系统性能.

In the internet of things(IoT)scenario,the edge server can effectively alleviate the problem of limited computing power of IoT devices,and how to ensure the energy supply of IoT devices has become one of the research hotspots.The combination of wireless energy transmission(WPT)and mobile edge computing(MEC)is a solution,but there is no guarantee that there is always a direct link between hybrid access point(HAP)and IoT devices.In order to deal with this problem,the intelligent reflective surface(IRS)is considered to assist wireless energy transmission and task unloading.In the multi-user MEC system,when the IoT device adopts binary unloading,it is a mixed integer non-convex problem to combine energy transmission time optimization,unloading decision and scheduling order to obtain the minimum system processing delay.Considering the channel difference between HAP and IoT devices,a two-layer iterative algorithm is used,and the computing power of MEC is used to minimize the processing delay of the system.The experimental results show that this method converges quickly,can effectively reduce the system processing delay,and can obviously improve the system performance with the help of IRS.