Research On Wireless Location Technology Of LTE System

In recent years, LTE industry chain has been mature, at the same time, there are more and more applications related to wireless location technology, thus the study about wireless location technology based on LTE system is more and more important. This thesis mainly studies wireless location technology related to the LTE system, and UKF algorithm performance optimization under NLOS environment. The main research is as follows:(1) In view of the great measurement in low SNR environment, this thesis puts forward OTDOA wireless location algorithm based on Alamouti coding. The scheme adopts double main charge mode, transmitting terminal Alamouti codes positioning reference signal of OFDM modulation, and the receiver gets the positioning reference signals by using the maximum ratio combining decoding received signal and OFDM demodulation. That is taking the antenna advantage of the LTE system, under the condition of the transmitted power is constant to obtain diversity gain.(2) Because that the error of UKF algorithm is great under the NLOS environments, and the error of the current node passes to the next node, this thesis puts forward a kind of NLOS error suppression algorithm based on UKF algorithm. That is to judge the error of every node and eliminate the nodes whose errors are greater than error threshold. And for these eliminated nodes, transcendental value replaces state estimate value. The important and difficult point of the algorithm is how to choose the error threshold. The error threshold can be set according to the prior information, or be set according to eliminating frequency.(3) Because that under different mobile communication environment, single location methods usually have different error characteristics, in this thesis, the hybrid location technologies are discussed. Data fusion technology and several mainstream hybrid location methods are introduced, and through the MATLAB simulation platform the performance of the hybrid location algorithm based on UKF algorithm is verified.For the first two research point, this thesis carries on the simulation experiment are in MATLAB platform. The results show that the positioning performance of the proposed optimization algorithm is better than the original algorithm, and positioning accuracy is improved.