Eigenvalue-based sensing and SNR estimation for cognitive radio in presence of noise correlation
2013 (English)In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 62, no 8, 3671-3684 p.Article in journal (Refereed) Published
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 standard-condition-number (SCN)-based decision statistics based on asymptotic random matrix theory (RMT) for the decision process. First, the effect of noise correlation on eigenvalue-based spectrum sensing (SS) is analytically studied under both the noise-only and signal-plus-noise hypotheses. Second, new bounds for the SCN are proposed to achieve improved sensing in correlated noise scenarios. Third, the performance of fractional-sampling (FS)-based SS is studied, and a method to determine 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 covariance matrix of the received signal is proposed. It is shown that the proposed SCN-based threshold improves sensing performance in correlated noise scenarios, and SNRs up to 0 dB can be reliably estimated with a normalized mean square error (MSE) of less than 1% in the presence of correlated noise without the knowledge of noise variance.
Place, publisher, year, edition, pages
2013. Vol. 62, no 8, 3671-3684 p.
Noise correlation, random matrix theory (RMT), signal-to-noise ratio (SNR) estimation, spectrum sensing (SS)
IdentifiersURN: urn:nbn:se:kth:diva-136550DOI: 10.1109/TVT.2013.2260834ISI: 000325988300015ScopusID: 2-s2.0-84886651585OAI: oai:DiVA.org:kth-136550DiVA: diva2:676373
QC 201406122013-12-052013-12-052014-06-12Bibliographically approved