Rail Transit LTE-M S1 Interface Monitoring And Early Warning System

In recent years,as the scale of rail transit LTE-M networks has become larger and larger,network monitoring of LTE-M has become more and more important.Once the LTE-M communication network fails,it will seriously threaten the safety of rail transit vehicles.Therefore,a system for monitoring the LTE-M network becomes more and more meaningful for the safe operation of the subway.The S1 interface connecting the base station and the core network can collect a large amount of effective information.Therefore,this project is based on the monitoring of the LTE-M S1 interface and combined with data analysis technology to develop a corresponding network monitoring system.This topic aims to improve the safe operation of rail transit.Without affecting the normal operation of the network,collect various data in the LTE-M network,filter effective information from the massive data,and use data analysis technology to analyze the data,The results obtained will help eliminate security risks in the network.The system will also provide the processed signaling data to the outside to help relevant personnel strengthen the management and maintenance of the network.Through the analysis of the signaling layer data,once the vehicle equipment failure causes the data to be abnormal,the system will give an early warning in time.This article summarizes the current status of the LTE-M S1 interface monitoring system,and systematically designs the software in accordance with the requirements of LTE-M in rail transit safety,combined with data analysis technology.The system mainly includes a data acquisition module,a data management module,an early warning module,and a data analysis module.The early warning module will classify the danger level and alarm according to the situation.The data analysis module also includes two small modules:network status analysis and network status prediction.The network status analysis includes two functions: main and backup core network detection and network-related parameter analysis.Use the data of the LTE-M S1 interface to monitor the handover of the active and standby core networks,analyze the correlation of daily network data,predict the relevant network conditions and give corresponding warnings.In the network condition prediction,the neural network is used to predict the data volume of the LTE-M S1 interface.The LTE-M core network disaster tolerance backup function detection designed in this subject can meet the core network disaster tolerance backup needs,and the neural network function has a certain degree of accuracy in predicting the amount of data.