﻿ 基于机器学习方法的无线信道特征的识别与区域划分 Identification and Region Division of Wireless Channel Characteristics Based on Machine Learning Method

Journal of Antennas
Vol.05 No.01(2016), Article ID:18126,7 pages
10.12677/JA.2016.51001

Identification and Region Division of Wireless Channel Characteristics Based on Machine Learning Method

Rengkang Wu

School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming Yunnan

Received: Jul. 7th, 2016; accepted: Jul. 25th, 2016; published: Jul. 28th, 2016

ABSTRACT

In this paper, using the machine learning method establishes the corresponding decision tree classification model for the characteristics of wireless channel. Using the real channel data tests the decision tree model and finds the classification results are better. Therefore, this machine learning method recognition model has high accuracy for wireless channel characteristics. Then we can use the model to divide the wireless channel data into region effectively, and the model also has statistical significance.

Keywords:Machine Learning, Wireless Channel, Decision Tree Model, Region Division

1. 引言

2. 机器学习模型的建立

3. 模型测试

Figure 1. The decision tree classification map of training set

Figure 2. The data described in figure

4. 无线信道区域的划分

4.1. 图形化描述以及“指纹”特征

Figure 3. Fingerprint feature of map data

Table 1. The partition table for test range zone

4.2. 区域划分

4.3. 区域划分的模型检验

5. 结论

Identification and Region Division of Wireless Channel Characteristics Based on Machine Learning Method[J]. 天线学报, 2016, 05(01): 1-7. http://dx.doi.org/10.12677/JA.2016.51001

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