Prediction of a New Kind of MR Data

Abstract

In the field of TD-LTE network problem analysis, compared with traditional methods such as DT(Driver Test) and CQT(Call Quality Test), MR (Measurement Report) has the advantages of comprehensive information and high efficiency, begins to get more and more attention and application. In order to solve the problem of limited open time of measurement data acquisition system, a data prediction method based on LSTM (Long Short-Term Memory) model is proposed. Selecting part of the MR parameters as the experimental object, training LSTM Model with measurement data in a district of Beijing. Experimental results show that the proposed method can predict MR data accurately. Compared with the traditional prediction model ARIMA (Autoregressive Integrated Moving Average Model), this method has lower prediction error and more stable generalization ability.