Maximum Eigenvalue Detection for Spectrum Sensing Under Correlated Noise

; ;

2014 • In *Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing 2014*

Peer reviewed

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Keywords :

Spectrum Sensing; Noise Correlation; Cognitive Radio; Random Matrix Theory

Abstract :

[en] Herein, we consider the problem of detecting primary users’ signals in the presence of noise correlation, which may arise due to imperfections in filtering and oversampling operations in a Cognitive Radio (CR) receiver. In this context, we study a Maximum Eigenvalue (ME) detection technique using recent results from Random Matrix Theory (RMT) for characterizing the distribution of the maximum eigenvalue of a class of sample covariance matrices. Subsequently,
we derive a theoretical expression for a sensing threshold as a function of the probability of false alarm and evaluate the sensing performance in terms of probability of correct decision. It is shown that the proposed approach significantly improves the sensing performance of the ME detector in correlated noise scenarios.

Disciplines :

Electrical & electronics engineering

Sharma, Shree Krishna ^{}; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)

Chatzinotas, Symeon ^{} ^{}; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)

Ottersten, Björn ^{}; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)

Language :

English

Title :

Maximum Eigenvalue Detection for Spectrum Sensing Under Correlated Noise

Publication date :

May 2014

Event name :

IEEE International Conference on Acoustics, Speech, and Signal Processing

Event organizer :

IEEE

Event place :

Florence, Italy

Event date :

4-9 May

Audience :

International

Main work title :

Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing 2014

Peer reviewed :

Peer reviewed

Available on ORBilu :

since 27 May 2014

Scopus citations^{®}

20

Scopus citations^{®}

without self-citations

without self-citations

18

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