PublisherIEEE Press. Institute of Electrical and Electronics Engineers
Rights accessRestricted access - publisher's policy
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.
CitationFont-Segura, J.; Vazquez, G.; Riba, J. Multi-frequency GLRT spectrum sensing for wideband cognitive radio. A: IEEE International Conference on Communication (ICC). "2011 IEEE International Conference on Communications". Kyoto: IEEE Press. Institute of Electrical and Electronics Engineers, 2011, p. 1-5.
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