Reference : Eigenvalue Based Sensing and SNR Estimation for Cognitive Radio in Presence of Noise ...
Scientific journals : Article
Engineering, computing & technology : Electrical & electronics engineering
http://hdl.handle.net/10993/3166
Eigenvalue Based Sensing and SNR Estimation for Cognitive Radio in Presence of Noise Correlation
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) > >]
Oct-2013
IEEE Transactions on Vehicular Technology
IEEE
62
8
3671 - 3684
Yes (verified by ORBilu)
International
0018-9545
[en] Spectrum Sensing ; SNR Estimation ; Noise Correlation ; Random Matrix Theory
[en] Herein, we present a detailed analysis of an eigenvalue
based sensing technique in the presence of correlated
noise in the context of a Cognitive Radio (CR). We use a
Standard Condition Number (SCN) based decision statistic based
on asymptotic Random Matrix Theory (RMT) for decision
process. Firstly, the effect of noise correlation on eigenvalue
based Spectrum Sensing (SS) is studied analytically under both
the noise only and the signal plus noise hypotheses. Secondly,
new bounds for the SCN are proposed for achieving improved
sensing in correlated noise scenarios. Thirdly, the performance
of Fractional Sampling (FS) based SS is studied and a method
for determining the operating point for the FS rate in terms
of sensing performance and complexity is suggested. Finally, a
Signal to Noise Ratio (SNR) estimation technique based on the
maximum eigenvalue of the received signal’s covariance matrix
is proposed. It is shown that proposed SCN-based threshold
improves sensing performance in correlated noise scenarios and
SNRs up to 0 dB can be reliably estimated with less than 1
% normalized Mean Square Error (MSE) in the presence of
correlated noise without the knowledge of noise variance.
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/3166
10.1109/TVT.2013.2260834

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