Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/631459
Title: A new joint eigenvalue distribution of finite random matrix for cognitive radio networks
Authors: Wensheng Zhang;Jian Sun;Hailiang Xiong;Di Chen
subject: joint eigenvalue distribution|finite random matrix|dual extreme eigenvalues|lower bounds|upper bounds|JED|cognitive radio networks|CSS scheme|cooperative spectrum sensing scheme
Year: 2016
Publisher: IEEE
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</italic> K</italic> &#x2265; 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.
URI: http://localhost/handle/Hannan/165240
http://localhost/handle/Hannan/631459
ISSN: 1751-8628
1751-8636
volume: 10
issue: 13
Appears in Collections:2016

Files in This Item:
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7564534.pdf369.14 kBAdobe PDFThumbnail
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Title: A new joint eigenvalue distribution of finite random matrix for cognitive radio networks
Authors: Wensheng Zhang;Jian Sun;Hailiang Xiong;Di Chen
subject: joint eigenvalue distribution|finite random matrix|dual extreme eigenvalues|lower bounds|upper bounds|JED|cognitive radio networks|CSS scheme|cooperative spectrum sensing scheme
Year: 2016
Publisher: IEEE
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</italic> K</italic> &#x2265; 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.
URI: http://localhost/handle/Hannan/165240
http://localhost/handle/Hannan/631459
ISSN: 1751-8628
1751-8636
volume: 10
issue: 13
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7564534.pdf369.14 kBAdobe PDFThumbnail
Preview File
Title: A new joint eigenvalue distribution of finite random matrix for cognitive radio networks
Authors: Wensheng Zhang;Jian Sun;Hailiang Xiong;Di Chen
subject: joint eigenvalue distribution|finite random matrix|dual extreme eigenvalues|lower bounds|upper bounds|JED|cognitive radio networks|CSS scheme|cooperative spectrum sensing scheme
Year: 2016
Publisher: IEEE
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</italic> K</italic> &#x2265; 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.
URI: http://localhost/handle/Hannan/165240
http://localhost/handle/Hannan/631459
ISSN: 1751-8628
1751-8636
volume: 10
issue: 13
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7564534.pdf369.14 kBAdobe PDFThumbnail
Preview File