Joint prediction method of base station traffic

Abstract

The invention provides a joint prediction method of base station traffic. The problem that the traditional linear algorithm is bad in prediction performance when the traffic data is nonlinear and hasa sudden change value is solved. The method comprises the following steps: firstly collecting traffic data from a base station as a data set, performing data preprocessing on an abnormal value and a missing value; decomposing processed data by adopting wavelet transform, enabling the traffic data to be smooth and easy to predict; performing single reconstruction on a sequence obtained through decomposition, wherein a low-frequency signal is predicted by adopting an echo state network model, and a high-frequency signal performs prediction by adopting an autoregression integral sliding average model; and finally performing linear accumulation on the prediction numerical value of the single sequence to obtain a final result. Compared with the single model prediction, the joint model method disclosed by the invention can reach better prediction, the reduced average absolute percentage error can achieve 6%, and the normalization root mean square error is reduced to a certain degree; the traffic data prediction accuracy of the base station is improved, and the network resource reasonable allocation can be improved.

Description

technical field [0001] The invention relates to the technical field of predicting base station flow by using ESN and ARIMA models, in particular to a base station flow prediction method based on wavelet decomposition transformation combined with echo network state. Background technique [0002] With the development of wireless communication technology, traffic forecasting has become one of the hottest research topics in recent years. Large-scale multimedia services are considered to be one of the most prominent features of smart cities. On the one hand, most users prefer to use mobile devices to surf the Internet, which will consume a lot of traffic data from wireless transmission. On the other hand, communication operators also need to know the amount of traffic data used in certain areas, and master the regional traffic data. Assignment levels. When the traffic peak exceeds the threshold that the equipment can withstand, the equipment in the base station should be replac...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to propose a joint prediction method of base station traffic, which solves the problem of low accuracy when the prior art is used to predict traffic data,

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