Analysis For Models Of LTE Traffic And Performance Evalution For LTE Networks

With the development of the fourth generation of mobile communication technology,domestic operators are gradually deploying and improving LTE networks.In order to make LTE network capacity tend to be the largest and network performance better,effective and reasonable network planning is imperative,meanwhile the analysis for traffic models and evalution for network performance are the bases for LTE network planning.On the other hand,with the rapid development of mobile Internet,mobile users' demands for data traffic will increase.Future mobile communication systems will be a user centric,open and integrated information infrastructure that provides personalized service experience,thus,the change of user profile has become the main driving force of the mobile communication networks' traffic trends.Although the overall traffic statistics in the mobile network can provide the basic rules of traffic amount,it cannot reveal the factors that effects the network load and network delay.In order to more accurately study the development trend of mobile and its influence on the network,this paper analyzes the traffic statistical model for each type of traffic and user profile models for each type of user,and evaluates LTE network performance under corresponding conditions.Firstly,according to the LTE service classification method based on QoS,four types of typical traffic are selected and the traffic statistical models of these four categories are analyzed in detail.Secondly,according to the traffic data,the traffic statistical model is set up,and the accurate traffic statistical model is obtained.Thirdly,the user profile model of every type of typical service is analyzed by combining the current user data.Lastly,based on the accurate traffic statistical model and user profile model,the performance of the network is evaluated by simulation,and the influence of the change of user's profile on the network performance is analyzed.The main contributions of this paper include:1.Study traffic statistical models of four typical traffic deeply.;2.Build a perfect user profile model;3.Propose network performance evaluation process based on OPNET Simulation;4.Analyze the impact of changes in user profile on the network performance.