A wireless channel model matching correction method based on map information

Abstract

The invention discloses a wireless channel model matching and correction method based on map information, comprising the following steps: carrying out drive test sampling on typical points within a planned area to obtain sampling data; acquiring map information within the planned area to obtain map data; Collect the working parameters of all base stations that can cover the planned area to obtain the collected data; collect the sampling data, map data and collected data to obtain the first data set; preprocess the first data set to obtain the second data set; The parameters of the regression matching model and the parameters of the classification matching model are determined according to the second data set; the final prediction values ​​corresponding to the wireless channel models of the non-sampling points within the planning area are obtained through the regression matching model and the classification matching model. The invention has the advantages of simple operation, full use of a typical statistical channel model, low computational complexity, wide application range, improved accuracy of the wireless propagation channel model, and the like.

Description

technical field [0001] The present invention relates to the field of wireless channels, more specifically, to a method for matching and correcting wireless channel models based on map information. Background technique [0002] During the network planning process of the cell of the mobile communication network, the operator needs to know the wireless channel model of the signal coverage area, and adjust the predicted value of the wireless channel model by comparing and evaluating the performance of different planning schemes, so as to achieve the goal of reasonably planning the cell. The propagation model of the wireless channel involves different landform contours (such as plains, valleys) and different man-made environments (such as urban areas, suburbs) that the signal passes through during transmission, so it is difficult to make accurate measurements at each location. [0003] Currently, there are roughly three methods for obtaining wireless channel propagation models. ...

AI Technical Summary

Problems solved by technology

One is to use the channel model standard formulated by the International Organization for Standardization (such as 3GPP, ITU). The advantage of this type of empirical statistical model is that it is simple and has a small amount of calculation. The scene is quite different

The second is a model based on measurement statistics, which obtains channel measurement data in multiple scenarios and frequencies to form a statistical model related to the planning environment and system parameters. In this method, operators need to carry out a lot of measurement work to generate corresponding channels. Characteristic and correction models, which are difficult to implement in the actual planning and design phase

The advantage of this deterministic model is that it can obtain more accurate propagation predictions than empirical statistical models, but it requires detailed information about the propagation environment and has high computational complexity, so it is mostly used in indoor range channel modeling

[0004] For the first method with a small amount of calculation, refer to the channel model standard of the International Organization for Standardization, most of which are based on the summary of typical scenarios and propagation models by foreign experts. Communication scenarios are often quite different from the actual situation, and professional personnel are required to modify and correct. The effect of correction is closely related to the personal experience of the planners, which makes it unable to meet the needs of the project.

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