基于MIMO的多无人机辅助移动边缘计算系统时延优化设计

Delay Optimization Design for Multi-UAVs Mobile Edge Computing Systems Based on MIMO

物联网数据的快速增长和物联网设备的计算限制催生了移动边缘计算(Mobile Edge Computing,MEC)解决方案。其中,无人机群的高机动性、易部署以及成本低的特点和多输入多输出(Multiple Input Multiple Output,MIMO)技术能够增强边缘计算网络的传输容量,缩短边缘计算网络的传输时延。该文在基于多无人机的多用户MIMO-MEC系统中通过联合优化无人机轨迹、地面用户卸载比、辅助无人机卸载比和辅助无人机数据分发比最小化整个周期的系统最大总时延。采用了连续凸优化技术和块坐标下降方法来解决其中的非凸问题。仿真结果讨论了影响系统时延的因素,并验证了算法的有效性及收敛性。

The rapid growth of data and the computing limitations of devices have spawned Mobile Edge Computing(MEC)solutions in Internet of Things.Among them,the high maneuverability,easy deployment and low cost of the Unmanned Aerial Vehicle(UAV)swarm and Multiple Input Multiple Output(MIMO)technology can enhance the transmission capacity and shorten the transmission delay in the MEC network.In this paper,the maximum total delay of the system are minimized by jointly optimizing the UAV trajectory,ground users’ratio of data offloaded,assisted UAV’s ratio of data offloaded and assisted UAV’sratio of data allocation in the multi-UAVs MIMO-MEC system,in which successive convex optimization technology and block coordinate descent method are used to solve the non-convex problem.The factors affecting the system delay are discussed,and the effectiveness and convergence of the algorithm is verified in the simulation results.