Design And Implementation Of Big Data Analytics System For Railway LTE Communication

This research presents development of big data analytics for optimization of LTE(Long Term Evolution)network for railways.Shuohuang Railway is one of the important and second largest supplier of coal to the west of Country to fuel the Chinese economy.To meet the increasing demands company decided to increase its long-haul railway operations capacity.By increasing its capacity mean more train journeys,with increasing number of journeys it is necessary to maintain efficient and safe operations of these long-haul trains.The decision for installation of LTE as railway communication system proved to be efficient,but the optimization of the newly installed system is mandatory so that problems and faults can be solved easily.Previously the optimization work was being carried out with existing computer systems,but it was difficult to collect,store and analyze huge amounts of data generated by the various sensor of LTE system.Consequently,making optimization almost difficult.Big data and related technologies have evolved since few years,and their capability to process bulky amounts of data has been proved,making it easy for the enterprises to generate insight of their systems for a better understanding of their system.The goal of this thesis is to present an understanding of the design and development processes needed to implement a Big Data-based analytics tool based on freely available open-source components in a robust,extensible manner.In this thesis,we have developed a web-based visualization system for optimizing the LTE system of Shuohuang railway.Data collected from various base stations is in XLS format having huge data sets as well as null or invalid values.The aim of this thesis is to design big data platform for getting insight into first ever LTE deployed at Shuohuang railway,with the objective of finding communication problems that may arise during the operations the system.Using data extracted from the LTE system it is processed and visualized in Cloudera CDH to get an insight of communication events such as Weak coverage area,Ping-Pong Handover,Interference,and KPIs(Key Performance Indicators)such RSRP,RSRQ,SINR etc.The practical application shows that the system can show the whole status of the communication network along the railway directly and vividly,and can carry out the troubleshooting of common communication problems,and greatly enhance the efficiency of communication transport dimension of the company,and have high practical value.Future work will focus on enriching the fault model and using big data technology to improve the data analysis speed.