Statistical covariance blind detection algorithm based on cholesky factorization in cognitive radio network

As the blind covariance detection algorithm has the shortcoming that the performance parameters are obtained using non-asymptotic method,a new blind detection algorithm was presented using cholesky factorization.Utilizing random matrix theory,the performance parameters was derived using non-asymptot...

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Bibliographic Details
Main Authors: Ying-xue LI, Shu-qun SHEN, Lang-tao HU, Qiu-cai WANG
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2012-11-01
Series:Tongxin xuebao
Subjects:
Online Access:http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2012.z2.015/
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Summary:As the blind covariance detection algorithm has the shortcoming that the performance parameters are obtained using non-asymptotic method,a new blind detection algorithm was presented using cholesky factorization.Utilizing random matrix theory,the performance parameters was derived using non-asymptotic method.The proposed method overcomes the noise uncertainty problem and performs well without information about the channel,primary user and noise.Numerical simulation results demonstrate that the performance parameters expressions are correct and the new detector outperforms the other blind covariance detectors.
ISSN:1000-436X