SVM-Based Spectrum Mobility Prediction Scheme in Mobile Cognitive Radio Networks
Joint Authors
Ma, Lin
Zhang, Zhongzhao
Wang, Yao
Chen, Jiamei
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-30
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Spectrum mobility as an essential issue has not been fully investigated in mobile cognitive radio networks (CRNs).
In this paper, a novel support vector machine based spectrum mobility prediction (SVM-SMP) scheme is presented considering time-varying and space-varying characteristics simultaneously in mobile CRNs.
The mobility of cognitive users (CUs) and the working activities of primary users (PUs) are analyzed in theory.
And a joint feature vector extraction (JFVE) method is proposed based on the theoretical analysis.
Then spectrum mobility prediction is executed through the classification of SVM with a fast convergence speed.
Numerical results validate that SVM-SMP gains better short-time prediction accuracy rate and miss prediction rate performance than the two algorithms just depending on the location and speed information.
Additionally, a rational parameter design can remedy the prediction performance degradation caused by high speed SUs with strong randomness movements.
American Psychological Association (APA)
Wang, Yao& Zhang, Zhongzhao& Ma, Lin& Chen, Jiamei. 2014. SVM-Based Spectrum Mobility Prediction Scheme in Mobile Cognitive Radio Networks. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1049451
Modern Language Association (MLA)
Wang, Yao…[et al.]. SVM-Based Spectrum Mobility Prediction Scheme in Mobile Cognitive Radio Networks. The Scientific World Journal No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-1049451
American Medical Association (AMA)
Wang, Yao& Zhang, Zhongzhao& Ma, Lin& Chen, Jiamei. SVM-Based Spectrum Mobility Prediction Scheme in Mobile Cognitive Radio Networks. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1049451
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1049451