Radio Access Control And Resource Allocation For Massiveconnection Service In Wireless Networks

With the explosive growth of the number of services and devices for mobile Internet and Internet of things,the access and core network of mobile communication networks are facing great transmission and service pressure.The fifth generation mobile system network(5G)has become a global research.5G network will gradually evolve into a heterogeneous interconnection network,its service include a variety of applications between people,between people and things and between things.The rapid development of Mobile Internet and Internet of things claim for higher access capacity of the future of wireless network.In order to support a variety of services requirements and ensure the efficiency of network management and data transmission in different scenarios,the effective carrying a variety of services in heterogeneous interconnection network will be promising,and the first step is how to proceed effective access.The study of intelligent wireless access issues in current cellular network is just applicable.On the other hand,the existing mechanism cannot adapt to the flexible traffic scheduling and efficient data forwarding requirements of mobile Internet and Internet of things.As the most important form of Internet of Things under huge number of connections scenarios,the access process of M2 M has been obtained the academic and industrial attention.The number and density of M2 M users' in the future cellular network will rise sharply.In the face of the massive access requirements of M2 M communication,simply relying on the macro base station to access will cause network congestion and overload.It will cause access delay,packet loss or even service interruption of M2 M users.Therefore,how to significantly improve the system's access capacity has become urgently to solve.And in order to guarantee the service requirements of different types of M2 M services,we need to design an appropriate wireless resource allocation management mechanism.As the access control and resource allocation mechanism plays an important role in the access process of M2 M users in huge number of connections scenarios,this paper studies the congestion and resource allocation in this process and puts forward the effective access congestion control mechanism and resources allocation strategy.The main achievements of this paper are as follows:1)According to the group characteristics of M2 M communication,an access mechanism of communication between MTC devices with congestion control is proposed by analyzing the existing research and protocol of M2 M communication.MTC devices establish communication connections and transmit data.The device received data will start the follow-up random access process.Based on this congestion control mechanism,it can effectively reduce the number of access collision and average access delay of MTC devices and improve the access efficiency of the devices while alleviating the access congestion of the base station.2)The MTC device in the overlapping coverage area can use the intelligent learning method to select access base station.It can minimize the average access delay of the MTC device.Before an MTC device in the overlapping area initiate an access request,it will independently observe,learn and obtain the accessible base station's signal strength and load,and select one of stations which can make the access delay lowest.The simulation results show that the selection of access base station mechanism based on Q learning can effectively reduce the average access delay and collisions of MTC devices and balance the load of base station to a certain extent.3)An efficient resource allocation scheme based on cooperative Q learning is proposed.Base stations learn and exchange information of environment and proceed resource allocation.It can use Monte Carlo UCT algorithm to search the optimal resource allocation strategy.The resource allocation scheme can obtain the optimal resource allocation strategy in a short learning time and can terminate the learning process at any time according to the delay requirement of different services.Compared with the traditional resource allocation scheme,it can effectively improve the system throughput and ensure the quality of service of MTC devices.Based on the analysis of the characteristics of M2 M communication,we design the congestion control mechanism and the access point selection and resource allocation scheme based on intelligent learning method.Our researches solve the problem of congestion and resource allocation of M2 M communication issues effectively and provide some new ideas and new methods to cellular wireless access problem.