Research And Development Of User Identification And Route Planning In LTE-A Air Interface Analyzer

With the change of the communication network architecture and the proliferation of 4G mobile phone users,the traditional signaling acquisition devices can no longer satisfy the current network requirements.And the demand of data service types of users has been more and more diversified,hence a monitoring analyzer is desiderated to collect and monitor air interface data.With this monitoring analyzer,the decoded data is used to identify the user's daily travel and traffic conditions,the user's travel time and space characteristics are extracted,and a user identification system is established,which has great research significance for specific user tracking.This thesis relies on the National Science and Technology Major Project “New generation broadband wireless mobile communication network”.Based on the background of LTE-A network,a set of user travel identification system oriented air interface signaling data is designed.A number of key technologies are adopted in this system,mainly including: using the protocol decoding scheme to obtain the signaling data in RRC protocol of users,using detection algorithm to eliminate redundant data,using the time-space clustering algorithm to identify the travel and stay characteristics of users.The modularization design method is introduced in this system,each system module implements the corresponding function independently.The coupling degree among systems could be effectively reduced.The main contributions of this thesis are as follows:Firstly,the RRC protocol in the air interface protocol stack is designed for decoding.A simple decoding module,a detailed decoding module,and a CDR synthesis module have been successfully designed,and the decoding accuracy is as high as 100%.Secondly,using detection algorithm to eliminate the repeated data,Ping-Pong effect data and drift data that affect user travel recognition.A total of twenty percent redundant data is excluded.Thirdly,using the time-space clustering algorithm to identify the characteristics of travel and stay about users and obtaining the time and space characteristics of user's travel behavior.The travel rules identified by system is highly consistent with the daily routines of the residents.Fourthly,the statistical analysis on the characteristics of user's travel behavior.Compared with the data in the comprehensive traffic report of the Chongqing,the data error of the user travel times is less than four percent.Fifthly,a set of design and implementation scheme which is used to identify user's travel behavior based on the data of the LTE-A air interface are put forward.It has higher practical value and great practical significance.At present,the system has been successfully applied to the terminal map strategic analysis project in Meishan.The system runs steadily and provides operational support for users' real-time tracking.