计算机工程与应用 ›› 2020, Vol. 56 ›› Issue (14): 82-87.DOI: 10.3778/j.issn.1002-8331.1904-0386

• 网络、通信与安全 • 上一篇    下一篇

基于MEC的蜂窝网络联合计算与无线资源管理

唐群,朱国强   

  1. 湖南省气象局 气象服务中心,长沙 410118
  • 出版日期:2020-07-15 发布日期:2020-07-14

Joint Computation and Radio Resource Management for Cellular Networks with Mobile Edge Computing

TANG Qun, ZHU Guoqiang   

  1. Meteorological Service Center, Hunan Meteorological Bureau, Changsha 410118, China
  • Online:2020-07-15 Published:2020-07-14

摘要:

移动边缘计算(MEC)是当下最有效的增强移动设备计算能力的方法,吸引了广大学者进行研究。为提高移动边缘计算的无线蜂窝网络性能,提出了一种基于移动边缘计算的无线蜂窝网络计算卸载和干扰管理集成框架。在该集成框架中,MEC服务器综合基于所有用户设备(UE)估算的计算开销和由MEC服务器自身估算的卸载开销做出卸载决策。然后MEC服务器再使用图着色进行PRB分配。最后基于卸载决策和PRB分配结果将MEC服务器的计算资源分配给用户设备UE。对该集成框架的仿真结果展现了该集成框架在不同系统参数下的有效性。

关键词: 移动边缘计算, 小型蜂窝网络, 卸载计算, 干扰管理, 资源分配

Abstract:

Mobile Edge Computing(MEC) is the most effective method to enhance the computing power of mobile devices, which has attracted a large number of scholars to research. In order to improve the performance of wireless cellular network for MEC, an integrated framework for computing offload and interference management of wireless cellular networks based on mobile edge computing is proposed in this paper. In this integrated framework, the MEC server makes the offloading decision according to the local computation overhead estimated by all User Equipments(UEs) and the offloading overhead estimated by the MEC server itself. Then, the MEC server performs the PRB allocation using graph coloring. The outcomes of the offloading decision and PRB allocation are then used to allocate the computation resource of the MEC server to the UEs. Simulation results are presented to show the effectiveness of the integrated framework with different system parameters.

Key words: mobile edge computing, small cell networks, computation offloading, interference management, resource allocation