title: SVM-based spectrum mobility prediction scheme in mobile cognitive radio networks.
abstract: 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.
authors.affiliation: Communication Research Center, Harbin Institute of Technology, Harbin 150080, China ; Communication Department, Shenyang Artillery Academy, Shenyang 110867, China.
authors.forename: Yao
authors.identifier: 0000-0002-2978-2400
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Communication Research Center, Harbin Institute of Technology, Harbin 150080, China.
authors.forename: Zhongzhao
authors.initials: Z
authors.lastname: Zhang
authors.affiliation: Communication Research Center, Harbin Institute of Technology, Harbin 150080, China.
authors.forename: Lin
authors.initials: L
authors.lastname: Ma
authors.affiliation: Communication Research Center, Harbin Institute of Technology, Harbin 150080, China.
authors.forename: Jiamei
authors.initials: J
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D006801:Humans; D009068:Movement; D060388:Support Vector Machine