Journal of Beijing University of Posts and Telecommunications

  • EI核心期刊

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2012, Vol. 35 ›› Issue (2): 90-93.doi: 10.13190/jbupt.201202.90.wuch

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GA-LSSVM Offline Learning in Cognitive Radios

WU Chun1,2,LI Ying3,YI Ke-chu1   

  1. 1. State Key Laboratory of Integrated Service Networks, Xidian University, Xi-an 710071, China;2. School of National Defense Technology, Southwest University of Science and Technology, Sichuan Mianyang 621000, China;3. Institute of China Electronic System Engineering Corporation, Beijing 100141, China
  • Received:2011-07-29 Revised:2011-10-17 Online:2012-04-28 Published:2012-01-05
  • Contact: Chun WU E-mail:soldier_wu@163.com

Abstract:

A cognitive radio (CR) learning and decision making method based on least squares support vector machine (LSSVM) is proposed by the demand of CR intelligent learning research. Genetic algorithm is adopted to search the hyper-parameters of LSSVM, and the CR learning model based on LSSVM is established. Through LSSVM offline learning on historical instances, the CR system gets the knowledge and uses it to guide future decisions. Simulation shows that GA-LSSVM algorithm can find out appropriate hyper-parameters within small generations and the LSSVM learning and decision making method can improve CR system’s performances effectively.

Key words: cognitive radio, intelligent learning, least squares support vector machine, genetic algorithm

CLC Number: