A new joint eigenvalue distribution of finite random matrix for cognitive radio networks. Issue 13 (1st September 2016)

• Record Type: Journal Article
• Authors: Zhang, Wensheng; Sun, Jian; Xiong, Hailiang; Chen, Di
• Is Part Of: IET communications. Volume 10:Issue 13(2016)
• Page Start: 1584
• Page End: 1589
• Publication Date: 2016-09-01
• Subjects: cognitive radio -- radio networks -- eigenvalues and eigenfunctions -- matrix algebra -- radio spectrum management -- signal detection -- cooperative communication; joint eigenvalue distribution -- finite random matrix -- cognitive radio networks -- JED -- dual extreme eigenvalues -- lower bounds -- upper bounds -- cooperative spectrum sensing scheme -- CSS scheme; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2015.0869
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : A new joint eigenvalue distribution (JED) based on dual extreme eigenvalues of finite random matrix is proposed in this study. Different from conventional JED based on K ( K ≥ 2) variables, only two variables are included in the proposed formulation. The upper and lower bounds of the new JED are determined. The new JED provides a simple and efficient way to deduce the distributions of key characteristics of finite random matrix, such as the extreme (largest and smallest) eigenvalues, standard condition number, and scaled largest eigenvalue. Moreover, a novel cooperative spectrum sensing (CSS) scheme based on the new JED is proposed for cognitive radio networks. The simulation results verify the proposed JED and the proposed CSS scheme can improve sensing performance.