Positioning method of LTE MR data

Abstract

The invention discloses a positioning method of LTE MR data. The method comprises the following steps: acquiring relevant information of a main service cell and relevant attributes of adjacent cells according to the acquired MR data and base station engineering parameters; performing indoor dispersion and positioning on sampling point data if the main service cell is an indoor sub-cell, or else performing MR data auxiliary positioning based on the adjacent cells according to adjacent cell conditions of the sampling point data. The method is high in practical operability. A plurality of methodsare combined, so that the problem that a large amount of MR data cannot be positioned due to field loss in the traditional method can be solved. The positioning analysis is carried out according to the received signal power, the transmitting power and the wireless signal propagation model in the MR data, and the precision of MR positioning is improved in combination with adjacent cell auxiliary positioning.

Description

technical field [0001] The invention relates to the fields of computers and mobile communications, in particular to a positioning method for LTE MR data. Background technique [0002] With the development of communication technology, the construction scale of LTE (Long Term Evolution, long-term evolution) network is gradually expanding, and the demand and construction of LTE wireless network are blowing out. With the new construction of 5G experimental network, 2 / 3 / 4 / 5G network coexists , the wireless environment is becoming more and more complex. The development of technology and the increase of network investment and construction bring users high-speed network experience and rich service applications. However, various problems in the wireless environment always affect users' perception. For operators, the traditional methods and ideas of wireless network optimization and evaluation, user complaint location, fault and hidden danger handling can no longer meet the actual ne...

AI Technical Summary

Problems solved by technology

[0005] At this stage, based on different characteristics such as base station type, base station location, user behavior, motion state, and signal characteristics, the method of separating MR data is too single, which leads to large errors in the actual application of these identification methods. At the same time, there is a lack of A set of systematic MR data positioning models and methods is difficult to apply in practice

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