Reference : Maximum Eigenvalue Detection for Spectrum Sensing Under Correlated Noise
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Electrical & electronics engineering
http://hdl.handle.net/10993/16859
Maximum Eigenvalue Detection for Spectrum Sensing Under Correlated Noise
English
Sharma, Shree Krishna mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Chatzinotas, Symeon mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Ottersten, Björn mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
May-2014
Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing 2014
Yes
International
IEEE International Conference on Acoustics, Speech, and Signal Processing
4-9 May
IEEE
Florence
Italy
[en] Spectrum Sensing ; Noise Correlation ; Cognitive Radio ; Random Matrix Theory
[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.
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/16859

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