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Blind localization of multiple primary users without number knowledge

Blind localization of multiple primary users without number knowledge
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摘要 A novel multiple PUs (Primary Users) localization algorithm was proposed, which estimates the number of PUs by SVD (Singular Value Decomposition) method and seeks non-cooperative PUs' position by executing k-mean clustering and iterative operations. The simulation results show that the proposed method can determined the number of PUs blindly and achieves better performance than traditional expectation-maximization (EM) algorithm. A novel multiple PUs (Primary Users) localization algorithm was proposed, which estimates the number of PUs by SVD (Singular Value Decomposition) method and seeks non-cooperative PUs' position by executing k-mean clustering and iterative operations. The simulation results show that the proposed method can determined the number of PUs blindly and achieves better performance than traditional expectation-maximization (EM) algorithm.
出处 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2012年第5期113-117,共5页 哈尔滨工业大学学报(英文版)
基金 Sponsored by the Scientific Research Program of Beijing Municipal Commission of Education ( Grant No. KZ2010100009009) Funding Project for Academic Human Resources Development in Institutions of Higher Learning Under the Jurisdiction of Beijing Municipality ( Grant No. PHR201008186) Scientific Research Fund of Heilongjiang Provincial Education Department ( Grant No. 11541083)
关键词 multiple primary user LOCALIZATION SVD ITERATIVE k-mean clustering multiple primary user localization SVD iterative k-mean clustering
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