Detection of Rank- P Signals in Cognitive Radio Networks With Uncalibrated Multiple Antennas

Spectrum sensing is a key component of the cognitive radio paradigm. Primary signals are typically detected with uncalibrated receivers at signal-to-noise ratios (SNRs) well below decodability levels. Multiantenna detectors exploit spatial independence of receiver thermal noise to boost detection pe...

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Bibliographic Details
Published in:IEEE transactions on signal processing 2011-08, Vol.59 (8), p.3764-3774
Main Authors: Ramirez, D., Vazquez-Vilar, G., Lopez-Valcarce, R., Via, J., Santamaria, I.
Format: Article
Language:English
Subjects:
Antennas
Applied sciences
Asymptotic properties
Cognitive radio
Covariance matrix
Detection, estimation, filtering, equalization, prediction
Detectors
Eigenvalues and eigenfunctions
Exact sciences and technology
generalized likelihood ratio test (GLRT)
Information, signal and communications theory
macimum likelihood (ML) estimation
Mathematical models
Maximum likelihood estimation
Minimization
Noise
Radio
Receivers
Signal and communications theory
Signal representation. Spectral analysis
Signal to noise ratio
Signal, noise
spectrum sensing
Telecommunications and information theory
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Summary:Spectrum sensing is a key component of the cognitive radio paradigm. Primary signals are typically detected with uncalibrated receivers at signal-to-noise ratios (SNRs) well below decodability levels. Multiantenna detectors exploit spatial independence of receiver thermal noise to boost detection performance and robustness. We study the problem of detecting a Gaussian signal with rank- P unknown spatial covariance matrix in spatially uncorrelated Gaussian noise with unknown covariance using multiple antennas. The generalized likelihood ratio test (GLRT) is derived for two scenarios. In the first one, the noises at all antennas are assumed to have the same (unknown) variance, whereas in the second, a generic diagonal noise covariance matrix is allowed in order to accommodate calibration uncertainties in the different antenna frontends. In the latter case, the GLRT statistic must be obtained numerically, for which an efficient method is presented. Furthermore, for asymptotically low SNR, it is shown that the GLRT does admit a closed form, and the resulting detector performs well in practice. Extensions are presented in order to account for unknown temporal correlation in both signal and noise, as well as frequency-selective channels.
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2011.2146779