Resource Management Method Based On Optimal Virtual Gateway And MEC In Machine-Type Communication

With the rapid development of the Internet of Things(IoT),a large number of machine-type communication devices(MTCDs)begin to appear in communication networks.The exponential growth of the number of MTCDs and unique communication characteristics bring many challenges to the traditional cellular network architecture and resource management methods,including network congestion,spectrum resources insufficient and insufficient computing and storage resources of MTCD.In response to these challenges,this paper focuses on the resource management aspects of MTC scenarios,which mainly include the following three aspects:(1)This paper first conducts a comprehensive analysis of the characteristics of MTC.Sparse Code Multiple Access(SCMA),Cognitive Radio(CR)and Mobile Edge Computing(Mobile Edge Computing,MEC)three technologies are used for machine-type communication,respectively to solve network congestion,Insufficient spectrum resources and MTCDs' own resource constraints.(2)To alleviate the problems of network congestion and insufficient spectrum resources,this paper proposes a cognitive SCMA system model based on the best virtual gateway.This model divides machine-type communication devices(MTCDs)into independent clusters based on Qo S requirements and geographic location.In each cluster,cognitive radio technology is used to perceive LTE users who may provide idle spectrum resources,which are defined as virtual gateways.Then the best virtual gateway is selected according to the rule of maximum satisfaction.The spectrum provided by the best virtual gateway is divided into multiple subcarrier groups,and design an optimal matching algorithm between MTCDs and subcarrier groups.The MTCD users use the matched sub-carrier group in the frequency domain SCMA mode and send the data to the best virtual gateway,and finally sent to the macro base station by the best virtual gateway.By building a link-level simulation platform for simulation,the simulation results show that the proposed scheme can effectively improve the spectrum utilization and throughput of the system.(3)In order to solve the resource limitation problem of Machine-Type Communications Device(MTCD),this paper applies Mobile Edge Computing(MEC)technology to machine-type communications.First,set up a Software Defined Network(SDN)controller in the macro base station,divide its coverage into multiple areas,and set up a small base station equipped with an MEC server in each area.Secondly,in order to determine the optimal task flow intensity in each region,the small cell is modeled as an M/M/1/ ?queuing model with different average service rates.Combining the two factors of average waiting time delay and energy consumption,the system loss model is established and solved by an iterative dichotomy algorithm.Third,the SDN controller counts the number of overloaded areas and areas with free resources according to the actual task flow intensity and the solved optimal task flow intensity.Finally,a cross-domain offloading algorithm is designed according to the energy loss coefficient of the MEC server and the distance between different regions.When some areas are overloaded and some areas have free resources,the SDN controller issues scheduling instructions to users in the overloaded areas according to the cross-domain offloading algorithm proposed in this paper,and these users use the frequency domain Sparse Code Multiple Access(SCMA)method for cross-domain offloading,and the MEC servers of the entire system work together.The simulation results show that the scheme proposed in this paper can make the system resource allocation more balanced and achieve the goal of energy saving.