Nonlinear interpolation prediction method of radio signal propagation

Abstract

The invention discloses a nonlinear interpolation prediction method of radio signal propagation, which relates to the technical field of wireless communication, in particular to the technical field of predicting the coverage propagation of the radio signal. The method comprises the following steps: analyzing drive test data, acquiring the weight factor of the influence of each drive test data point on other points on a propagation path, dividing a prediction region into triangular tiny regions spliced without seams, carrying out nonlinear interpolation on the triangular regions adjacent to actually tested data according to the weight factor, acquiring predicted field intensity values of the regions, calculating the mid-value field intensity of other triangular regions in a curve-fitting method by the actually tested and predicted values, and outputting the field intensity coverage prediction result of the whole prediction region. The invention realizes the high-precision prediction of the radio signal propagation at low cost and is suitable for being used in wireless mobile communication.

Description

technical field [0001] The present invention relates to the technical field of wireless communication, in particular to the technical field of predicting the coverage and propagation of wireless signals. Background technique [0002] At present, the existing wireless signal propagation prediction methods at home and abroad are mainly divided into two categories, namely empirical prediction methods and theoretical prediction methods. They all treat the coverage prediction of the median signal field strength distribution as a positive problem, that is, pre-establish the propagation model and its parameters, and then calculate the attenuation of the median signal field strength through different technical means. These studies have their own characteristics and strengths, but there are also some inherent deficiencies and limitations. The empirical method is mainly to establish a set of empirical formulas about propagation loss through the prior understanding of the propagation ...

AI Technical Summary

Problems solved by technology

However, the realization and practical application of the theoretical prediction method is very difficult. The primary problem it faces is to establish a high-precision terrain and object database for each specific communication environment. This is not only time-consuming and expensive for the algorithm

In addition, even if there is a very high-precision terrain and object database, it is impossible to include all the details, especially because there are many time-varying factors in the environment, and it is often such details that will greatly affect the prediction results of the theoretical model

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