MR (Measurement Report) data indoor and outdoor separation method based on statistic model

Abstract

The invention discloses a MR (Measurement Report) data indoor and outdoor separation method based on a statistic model. The MR data indoor and outdoor separation method comprises the steps of: aiming at MR sampled data of each cell of an outdoor macro station, carrying out characteristic value statistics of received signals, which comprises statistics of a main cell level; and carrying out separation of a mixed Gaussian distribution and probability calculation, and according to an indoor probability, obtaining a corresponding indoor and outdoor separation result. Moreover, the MR data indoor and outdoor separation method supports combination of various factors of the main cell level, a main and adjacent level difference, the number of adjacent cells and the like, and by a combined model, an indoor and outdoor judgment result is judged and output; and judgment methods at other angles also can be integrated. According to the MR data indoor and outdoor separation method disclosed by the invention, data characteristics which are shown by signal intensity and a signal number of the MR data in a statistical sense and are combined by two indoor and outdoor normal distributions are utilized, and probabilities that different signal intensity and different signal numbers occur in a door or outside a door can be calculated, so that the method of separating the MR data according to signal characteristics is more feasible, and accuracy of indoor and outdoor separation of the MR data is improved.

Description

technical field [0001] The invention relates to the technical field of LTE communication, in particular to a statistical model-based indoor and outdoor separation method for MR data. Background technique [0002] Currently, the LTE (Long Term Evolution, long-term evolution) network wide coverage construction has been completed, and the RSRP indicators of urban roads have reached the target requirements of wide coverage. The construction and optimization of deep network coverage has become the main work. Statistics show that more than 70% of mobile communication traffic occurs indoors. If there are problems such as weak coverage indoors, it will seriously affect user experience. Therefore, it is possible to quickly and accurately identify and locate urban indoor deep weak coverage areas , is the primary task to solve the depth coverage. [0003] The traditional manual indoor sweeping test is time-consuming, labor-intensive, extremely expensive and incomplete, and cannot effe...

AI Technical Summary

Problems solved by technology

Among them, the separation method based on signal characteristics is based on the different characteristics of indoor and outdoor signals. The indoor signal is weakened due to being blocked by the wall. Compared with the outdoor signal, the signal strength is weaker and the number of signals is less. Based on this, indoor and outdoor signals can be distinguished. However, it is very difficult to distinguish each piece of MR data and set the distinction threshold, because the characteristic thresholds of indoor and outdoor MR data in different environments are different

Therefore, the MR data separation method based on signal characteristics currently lacks further theoretical and method guidance, and it is still difficult to be practical.

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