Research On Access Selection Technology For 5G Heterogeneous Network Architecture

The fifth generation mobile networks(5G)will apply heterogeneous network architecture that integrates LTE,Wi-Fi and other radio access technologies(RATs)to achieve seamless connection between user terminals requesting different types of services and networks.5G heterogeneous network system can support at least a thousand times of traffic,connect hundreds of billions of wireless devices,and meet the demands of diverse services.However,the deeper heterogeneity of wireless networks and the dense distribution of massive terminal devices have brought many challenges to the network selection in 5G heterogeneous wireless networks(HWNs).In the future 5G system,how to reasonably organize the network selection under the HWNs and realize the optimal utilization of network resources is an urgent problem in radio resource management(RRM).Although the network selection algorithm based on the traditional game theory such as zero-sum game has the ability to grasp the essence of competition,it is ideal in practical application.In addition,the random movement of users and the inaccurate information of networks as well as personalized service requirements will also affect the network selection results.Therefore,an effective network selection algorithm needs to adaptively optimize the access selection of users according to the realtime status of users and networks.In order to efficiently utilize network resources and improve user experience,this thesis first introduces a heterogeneous network selection algorithm for novel 5G services based on evolutionary game,named NS-EG.It applies analytic hierarchy process to analyze service requirements,and considers the cost of users accessing the network to form the payoff function in the game.Simulation results show that compared with mainstream algorithms,the NS-EG algorithm achieves better performance in terms of average energy efficiency,average delay and overall packet loss rate.Because the coverage of different networks is different,and the motion status of users will affect the network selection results.Therefore,considering that the motion speed of edge users is randomly variable,we propose an adaptive multiservice heterogeneous network selection scheme in mobile edge computing(MEC)named MSNS in the thesis.MSNS combines the advantages of fuzzy logic in the dynamic adaptability and multiple attribute decision making(MADM)in accuracy and stability.It solves the problem of optimal network access for edge users who request different services in any motion state,and provides a universal method for edge users to select networks in HWNs.Simulation results show that the MSNS algorithm can adaptively switch to the optimal network according to the service requirements requested by the edge users,and has high scalability in the future user-centric network architecture.