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Support vector machine-based cabin interior path loss prediction method

A support vector machine, path loss technology, applied in power management, wireless communication, electrical components, etc., can solve problems such as measurement difficulties

Inactive Publication Date: 2014-04-09
TIANJIN UNIV
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Problems solved by technology

Due to the special environment of the engine room, it is difficult to carry out a large number of measurements while retaining the original appearance of the engine room

Method used

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  • Support vector machine-based cabin interior path loss prediction method
  • Support vector machine-based cabin interior path loss prediction method
  • Support vector machine-based cabin interior path loss prediction method

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Embodiment Construction

[0040] In order to solve the shortcomings of inconvenient measurement and inaccurate prediction of the existing path loss due to the small space inside the nacelle, the present invention uses the path loss values ​​of the measured points inside the nacelle to train the model on the basis of the support vector machine (SVM) theory. The model is then used to predict pathloss values ​​at unmeasured points inside the nacelle. The results show that the path loss prediction based on support vector machine is more accurate than the surface fitting prediction method.

[0041] In order to simplify the measurement difficulty and reduce the number of measurements, and improve the accuracy of prediction. The invention proposes a path loss prediction model based on support vector machine. The field strength inside the nacelle is mainly affected by two aspects: path loss caused by distance attenuation and shadow fading caused by obstacles. Through the analysis, it can be known that the pa...

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Abstract

The invention belongs to the field of wireless communication. In order to decrease the difficulty of measurement and the number of measurement and increase the accuracy of prediction, the technical scheme adopted by the invention is a support vector machine-based cabin interior path loss prediction method, which includes the following steps: distributed MISO (multi-input single-output) data is measured, and MISO is a multi-input single-output system; MISO path loss is calculated; the path loss PL data of each connection is adopted as training sample data, eight path loss values around a certain position as a center are adopted as eight-dimensional input variables xi in a training sample set (xi, yi), the path loss value of the position is adopted as an output variable yi, a support vector machine regression algorithm is adopted to process the training sample set data (xi, yi), and the Gaussian radial basis function is adopted as a kernel function in the regression model of the support vector machine regression algorithm. The support vector machine-based cabin interior path loss prediction method is mainly applied to cabin interior path loss prediction.

Description

technical field [0001] The invention belongs to the field of wireless communication, and is the key technology of the next generation multi-antenna mobile communication system-channel modeling technology. The channel propagation model is one of the foundations of network planning, and its ability to accurately predict path loss determines the quality of network planning to a certain extent. Specifically, it relates to a method for predicting path loss inside the cabin based on support vector machines. Background technique [0002] At present, the measurement results of the large aircraft scene are concentrated in the narrowband and low frequency bands, and the frequency bands include 1.8GHz, 2.1GHz, 2.4GHz and so on. The measurement of some high-frequency bands is also mainly the case of single-transmit-single-receive (SISO). The analysis parameters mainly focus on the field strength. The main analysis parameter results are: large-scale parameters (path loss, shadow fading...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04W52/00
Inventor 侯春萍赵晓楠汪清
Owner TIANJIN UNIV
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