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Telephone traffic prediction method and apparatus

A forecasting method and traffic volume technology, applied in network traffic/resource management, electrical components, wireless communication, etc., can solve problems such as the use of forecasting tools, difficulty in reflecting, and low forecasting accuracy, and achieve accurate real-time traffic forecasting Effect

Active Publication Date: 2009-06-10
CHINA MOBILE GRP BEIJING +1
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AI Technical Summary

Problems solved by technology

When traffic forecasting is performed, these data bases are smoothed and filtered by time, so it is difficult for this algorithm to reflect sudden changes in network traffic conditions; and because its data bases are at the cell level, therefore As a result, the prediction accuracy is low, and only the traffic changes of network elements with a level larger than the cell can be predicted
[0007] The existing mobile network forecasting algorithm can only be used as an offline forecasting tool, such as predicting the traffic volume of tomorrow at a certain time today, and cannot be used as a real-time (less than an hour, or even finer-grained) forecast tool use

Method used

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  • Telephone traffic prediction method and apparatus
  • Telephone traffic prediction method and apparatus
  • Telephone traffic prediction method and apparatus

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Embodiment Construction

[0062] The embodiment of the present invention provides a method for predicting traffic volume, which predicts future traffic volume (or other key indicators) in time and space based on MR analysis and processing of massive measurement reports. Among them, the definition of space-time is one-dimensional time series and two-dimensional geographic grid. The MR is the measurement data of the channel quality reported by the mobile terminal, which is transmitted through the Slow Associated Control Channel (SACCH) and used as a decision basis for network handover and power control. The MR includes measurement data of a primary serving cell (Serving Cell, primary cell for short) and a neighboring cell (Neighbour Cell). The default upload period of the measurement report is 0.48S. Since the communication interface between the Base Transceiver Station (BTS) and the Base Station Controller (BSC) - the Abis interface is not a standard interface, different equipment manufacturers The tra...

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Abstract

The invention discloses a method and a device for predicting traffic, which predicting the traffic based on a mass measurement report and comprises: determining the grid in which a measurement report MR is positioned during reporting according to the report position of the measurement report received, wherein the grid is obtained by dividing the geographic area of the traffic to be tested in advanced; counting the MRs in all time periods of each grid according to the report time and the grid of the MR; acquiring the number of MRs in the M adjacent time periods of a current time period in each grid and calculating a predicted value of the traffic in the current time period in each grid by using a time sequence prediction algorithm. The method and device realize real-time, fine-granularity and high-precision traffic prediction.

Description

technical field [0001] The present invention relates to the field of mobile communication, in particular to a method and device for predicting traffic volume based on measurement reports (Measurement Report, MR). Background technique [0002] Due to the mobility of terminals in the mobile communication network, the distribution of user services in the mobile communication network is two-dimensional, that is, there are two dimensions of time and space, and predicting the traffic distribution of the mobile communication network is the current mobile communication network planning. and a key issue of security. [0003] At present, the traffic forecast of the mobile communication network is mainly based on the forecast of the time dimension. The data is based on the count value of the counter counted by the Operations & Maintenance Center (OMC), and these count values ​​are stored in the format of time series. of. [0004] The spatial granularity of these count values ​​is usu...

Claims

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Application Information

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IPC IPC(8): H04W24/08H04W24/10H04W64/00
CPCH04W28/02H04W24/08
Inventor 杨晓范王文明吴晓梅周莅涛王晋龙李欣然乔琳郭同文马云飞刘莉莉高翔黄卫正孙向光王鹏
Owner CHINA MOBILE GRP BEIJING
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