Detection of the Primary User's Behavior for the Intervention of the Secondary User Using Machine Learning

被引：3

作者：

Zambrano Soto, Deisy Dayana ^{[1
]}

Salcedo Parra, Octavio Jose ^{[1
,2
]}

Lopez Sarmiento, Danilo Alfonso ^{[1
]}

机构：

[1] Univ Distrital Francisco Jose de Caldas, Internet Res Grp, Fac Engn, Bogota, Colombia

[2] Univ Nacl Colombia, Fac Engn, Dept Syst & Ind Engn, Bogota, Colombia

来源：

FUTURE DATA AND SECURITY ENGINEERING, FDSE 2018 | 2018年 / 11251卷

关键词：

Cognitive Radio; KNN; LR; Machine learning; Primary users (PU); SVM;

D O I：

10.1007/978-3-030-03192-3_15

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The predictive analysis for the spectral decision with automatic Learning is a task that is currently challenging. Some automatic Learning techniques are shown in order to predict the presence or absence of a primary user (PU) in Cognitive Radio. Four machine learning methods are examined including the K-nearest neighbors (KNN), the support vector machines (SVM), logistic regression (LR) and decision tree (DT) classifiers. These predictive models are built based on data and their performance is compared with the purpose of selecting the best classifier that can predict spectral occupancy.

引用

页码：200 / 213

页数：14

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