Research On User Clustering Oriented To Temporary Hotspot Resource Allocation

In recent years,with the continuous growth of wireless services,high data capacity,high data rate,low transmission delay and long battery life have become the characteristics that mobile communication networks must have in the future,and 4G network technology has been gradually replaced by 5G technology.Facing the development of network technology and the popularization of smart devices,it has become the basic needs of ordinary users to carry out network activities anytime,anywhere.In the wireless network service scenario,temporary hotspots(temporary hotspots)are a kind of scenes generated to support large special events.Due to the limitation of time and space resources,how to better coordinate resource expenditures in the scenario to better serve users' network activities has become a problem worth studying in the context of the development of new 5G technologies.Temporary hotspot scenes often have the characteristics of large user group density and frequent network activities.In view of such a scenario,the service pressure of the macro base station around the scenario is large,and it cannot meet the user needs in the scenario well.Due to the existence of active and inactive periods,simply increasing the radio access network load-bearing resources in the scenario cannot effectively solve the problem.Because the radio access network resources serving such temporary scenarios will be idle during the inactive period,during the active period,it may not be able to meet the basic network needs of users in the scenario because of the insufficient carrying capacity of the base stations around the scenario.To comprehensively analyze the problems in temporary hot spots,this paper proposes a compensation service scheme for unmanned aerial vehicles based on real-time clustering of user network requirements.From the perspective of the user's network requirements,the classic real-time stream clustering algorithm is improved from the perspective of density definition and density threshold,through which the user is modeled based on physical location and network requirements,and the clustering results are dynamically output.Based on the cluster output,the user cluster establishes a combined optimization problem to solve the optimal coverage area of the unmanned aerial vehicle that mounts the small base station,and relieves the service pressure of the macro base station by allowing users to offload from the macro base station.Finally,the article builds a specific temporary hot spot scene based on the packet capture data,and establishes a signal transmission loss model within the scene.Experimental simulation analysis verifies that the UAV compensation service scheme based on real-time streaming clustering can effectively reduce the service pressure of fixed base stations in temporary hot spots during active periods.