A method and system for positioning in td-lte grid based on mr data

Abstract

The present invention relates to a method and system for positioning in a TD-LTE grid based on measurement report (MR) data. The positioning method includes: dividing the mobile coverage area into a plurality of square TD-LTE grids; collecting signal strength and signal quality received from a base station at reference points in each of the plurality of square TD-LTE grids; based on the The signal strength, signal quality and the position information of the reference point are used to generate fingerprint data; the fingerprint data is corrected to construct a fingerprint database; the MR data to be positioned is analyzed to obtain the fingerprint feature information of the MR data; fingerprint distance matching is adopted An algorithm is used to compare the fingerprint feature information with the fingerprint database to locate the MR data.

Description

technical field [0001] The present invention generally relates to the technical field of communication, and more specifically, relates to a method and system for positioning in a TD-LTE grid based on MR data. Background technique [0002] With the advent of the 4G era, the number of mobile users has shown explosive growth, and people's demand for wireless positioning services has become increasingly prominent. Therefore, providing optimization methods based on location positioning technology has become a current research hotspot. Traditional wireless network optimization methods are usually carried out by analyzing network performance data and road test data. However, this method has certain suddenness and uncertainty, so it requires a lot of human and material resources Complaints and feedback can only be responded to. [0003] Although the measurement report (MR) data can reflect the coverage of the cell, since there is no location information, the MR data is mainly appli...

AI Technical Summary

Problems solved by technology

[0004] There are three main traditional positioning technologies, which are based on time of arrival (TOA) positioning method, triangulation positioning method and multi-point positioning method, but the positioning accuracy of these three positioning technologies cannot meet the requirements of the US Federal Communications Commission ( FCC) in 2001 proposed positioning accuracy requirements (that is, the positioning probability of 125 meters reaches 67%, and the positioning probability of 100 meters reaches 50%)

At the same time, the existing positioning technology cannot overcome the errors caused by noise interference such as multipath fading and shadow effect

In addition, the existing positioning technology needs to add additional hardware devices for precise time synchronization and angle measurement, thus increasing the cost of network optimization

Although these algorithms have played an important role in promoting the solution of positioning problems, they cannot fully consider all aspects of live network applications.

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