Multi-Frequency GLRT Spectrum Sensing for Wideband Cognitive Radio

The problem of spectrum sensing in multi-frequency cognitive radio systems is addressed. We show that as the sensed bandwidth increases, the primary user detection is governed by a low signal-to-noise ratio (low-SNR) regime. By means of low-SNR approximations, we show that the optimal generalized li...

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Bibliographic Details
Main Authors: Font-Segura, J., Vazquez, G., Riba, J.
Format: Conference Proceeding
Language:English
Subjects:
Cognitive radio
Detectors
Kernel
Maximum likelihood estimation
Noise
Wideband
Online Access:Request full text
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Summary:The problem of spectrum sensing in multi-frequency cognitive radio systems is addressed. We show that as the sensed bandwidth increases, the primary user detection is governed by a low signal-to-noise ratio (low-SNR) regime. By means of low-SNR approximations, we show that the optimal generalized likelihood ratio test (GLRT) only depends on the second order statistics of the observations and on a shaping kernel that highlights the relevant parameters required for detection. Furthermore, the ML estimates of the unknown model parameters are derived for multi-frequency systems, which allow closed-form expressions for the GLRT statistic. The detection performance and the kernel interpretation are supported with simulation results.
ISSN:1550-3607
1938-1883
DOI:10.1109/icc.2011.5963314