Method and device of predicting propagation path loss based on classification fitting

A technology of path loss and classifier, which is applied in the field of communication, can solve the problems of low applicability of propagation model, low utilization rate of data validity, inability to adapt propagation model, etc., achieve high prediction accuracy, reduce various defects, predict The results are more accurate and more effective

Active Publication Date: 2016-03-23
SHANGHAI HUAWEI TECH CO LTD
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Problems solved by technology

[0004] Practice has found that for deterministic propagation models, the ray tracing technology used has the defects of large amount of calculation and low efficiency; moreover, the propagation model obtained by ray tracing technology generally adopts one propagation model for one planning area, which cannot be adaptively based on the propagation Features are adapted to the corresponding propagation model, resulting in low applicability of the propagation model
For the empirical (statistical) propagation model, it has defects such as low simulation accuracy and low utilization rate of data validity by propagation model correction

Method used

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  • Method and device of predicting propagation path loss based on classification fitting
  • Method and device of predicting propagation path loss based on classification fitting
  • Method and device of predicting propagation path loss based on classification fitting

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Embodiment 1

[0058] Embodiment 1 of the present invention provides a method for predicting propagation path loss based on classification fitting. This method is a predictive calculation method for the propagation characteristics between the transmitter and the receiver. This method uses the propagation characteristics to perform clustering, uses non-parametric fitting method for each class to obtain the propagation model, and builds a random forest classifier. The random classifier adaptively matches each propagation model to each pair of transmitter and receiver, and uses the matched propagation model to predict, and can obtain the finely predicted propagation path loss result.

[0059] Please refer to image 3 , the specific process of the method of the embodiment of the present invention may include:

[0060] 300 . Clean and filter the acquired measured data.

[0061] First of all, it should be noted that this step is optional. In the subsequent steps, all the acquired measured data ...

Embodiment 2

[0414] In order to better implement the above solutions of the embodiments of the present invention, related devices for coordinating the implementation of the above solutions are also provided below.

[0415] Please refer to Figure 18 , an embodiment of the present invention provides an apparatus 1800 for predicting propagation path loss based on classification fitting, which may include:

[0416] The characteristic calculation module 1801 is used to calculate the propagation characteristics of electromagnetic waves between the transmitter and the receiver according to the measured data;

[0417] Clustering processing module 1802, for clustering the measured data by using at least one propagation feature, and constructing a random forest classifier;

[0418] Model generation module 1803, used for performing non-parametric fitting on each type of measured data obtained by clustering to generate a corresponding propagation model;

[0419] The matching calculation module 1804...

Embodiment 3

[0435] An embodiment of the present invention also provides a computer storage medium, which can store a program, and when the program is executed, it includes some or all of the steps of the method for predicting propagation path loss based on classification fitting described in the above method embodiment.

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Abstract

Provided are a method and device of predicting propagation path loss based on classification fitting, aiming to increase the efficiency of building a propagation model, improve the accuracy of predicting propagation path loss, and facilitate adaptively coupling corresponding propagation models according to propagation characteristics. In certain feasible embodiments, the method comprises: computing the electromagnetic wave propagation characteristics between a transmitter and a receiver according to actual measurement data; utilizing at least one propagation characteristic to classify the actual measurement data, and building a random forest classifier; performing nonparametric fitting on each kind of clustered actual measurement data to generate corresponding propagation models; and utilizing the random forest classifier to adaptively couple corresponding propagation models according to the propagation characteristics between the transmitter and the receiver, and calculating the path loss between the transmitter and the receiver.

Description

technical field [0001] The invention relates to the field of communication technology, in particular to a method and device for predicting propagation path loss based on classification fitting. Background technique [0002] Evaluating wireless network coverage through planning tools is one of the important means for high-quality wireless network planning and optimization. The simulation accuracy of basic indicators (such as level value, interference, rate) of various generations of communication technologies (such as 2G / 3G / 4G) is the key to the accuracy of coverage evaluation. The core part of the simulation of each basic index is the calculation of the wireless electromagnetic wave propagation path loss between the transmitter and the receiver. The industry mainly relies on the propagation model (PropagationModel) to estimate the propagation path loss. The propagation model is a mathematical model obtained through a large amount of data or calculation methods. The process ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W16/18H04W24/06
CPCH04W16/18H04W24/06
Inventor 李小龙何峰闵冬高源王灿
Owner SHANGHAI HUAWEI TECH CO LTD
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