Research On Deployment Method Of Small Cell In Ultradense Heterogeneous Network

With the rapid growth of data transmission,the needs of users have also changed greatly.The survey shows that one of the main characteristics of mobile Internet is that the business volume that occurs indoors accounts for an extremely high proportion of the total business volume.About 60% of voice services and more than 90% of data services occur indoors,resulting in strong indoor users' machines.Mobile network coverage requirements.At the same time,mobile data services have very high requirements for data transmission quality.Only when extremely high data rates and extremely low packet loss rates and delays are guaranteed at the same time,can users' increasing demands for high-quality multimedia services be met.Due to the rapid growth of data and changes in user requirements,traditional macro base station coverage methods are difficult to meet user requirements.At the same time,with the increase in the deployment of a single traditional macro base station,on the one hand,it has brought huge network construction and network operation costs,on the other hand,the interference between the base stations has caused the difficulty of adding new base stations,which has greatly increased the network.The difficulty of optimization.In view of the above problems,it has become a feasible solution to build a user-centric ultra-dense heterogeneous network by deploying small base stations that are cheaper and closer to users.In this paper,the deployment strategies of small cells in ultra-dense heterogeneous networks are studied in the following two stages.(1)In the network construction stage,aiming at the deployment of a single traditional macro base station,this paper studies the optimal deployment of small base stations in an ultradense heterogeneous network.Combined with the average user demand,the energy efficiency of the ultra-dense heterogeneous network is maximized by optimizing the number of small base stations deployed in the heterogeneous network and the corresponding transmission power.Because of the design of continuous variables and discrete variables for this optimization problem,it is modeled as a mixed integer nonlinear programming problem,and a feasible autofocus search algorithm is proposed based on this.This algorithm does not need to search all points in the search path concentration,so the implementation complexity is low,and the optimal number of small base stations and corresponding transmission power can be quickly found under the constraints of coverage and base station density.(2)In the network operation stage,considering the temporal and spatial differences of user requirements,based on the deployment of small base stations in ultra-dense heterogeneous networks,an energy-saving small base station planning strategy that dynamically adjusts the transmission power of small base stations is proposed to further improve network energy efficiency.In this stage,consider the bursty self-similar user model and small cell transmit power adjustment properties,decouple the energy-saving small cell planning strategy into two sub-problems of resource allocation algorithm and user association matching algorithm,and use allocation algorithm and improved The user matching algorithm solves these two subproblems,thereby solving the dynamic optimization problem of the transmission power of the energy-saving small base station,and further improving the energy efficiency of the ultra-dense heterogeneous network.(3)In this thess,the optimization problem of the optimal deployment strategy of small base stations based on the auto-focus search algorithm and the energy-saving base station planning strategy based on the two-stage sub-algorithm have been experimentally verified and analyzed.The experimental results are not difficult to find.The deployment strategy proposed in this article can reduce energy consumption and further improve the energy efficiency of the network.