Study Of High-speed Railway Network Coverage And Optimization Based On LTE System

More and more travelers are willing to prefer high speed railway as their first choice to go out. Because high speed railway is cheaper, more convenient and faster than other transportations, China has entered the high speed railway age. The increase of the speed and the emer gence of the new compartment bring efficient and comfort to people. At the same time, people put forward higher requirements to high speed railway’s wireless mobile communication system. In order to improve the quality of the signal and improve the customer’s satisfaction, we should come up with a dedicated network for coverage of high-speed rail in this particular scene.In this thesis, we obtained the influence on LTE network coverage through the analysis of high speed railway’s special scene. The solutions of LTE network coverage and network optimization are studied based on high-speed railway’s special scene. This thesis first analyzes the LTE system network architecture and key technologies such as OFDM and MIMO. These provide a certain theoretical basis to the research of this thesis. Then this thesis analyzes the high-speed railway’s LTE network coverage scene and discusses the various causes of affecting the high-speed railway’s LTE network coverage. Then the principle, process, method and content of the high-speed railway’s LTE network optimization are introduced and discussed, including coverage optimization, interference optimization, frequency optimization, access optimization and so on. Finally, this thesis gives solutions of network coverage ’s problems and site layout under high-speed railway’s special scene. Combining with high-speed railway project in Jiangsu region, it gives special network entrance optimization examples, coverage problem optimization examples, signal out of network problem optimization examples and CSFB optimization examples and so on. This thesis demonstrates the high-speed LTE wireless coverage solutions and network optimization method.We conclude that the proposed network coverage and network optimization are significantly better than others by using GENEX Assistant software to analysis the test data before and after.