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Spectrum sensing is a fundamental technology to detect the presence of primary user in cognitive radio networks. Usually, the requirements for spectrum sensing are very stringent. It requires that the spectrum sensing scheme has a good performance even in extremely low signal-to-noise ratio (SNR) environments. In this paper, we propose a novel spectrum sensing method based on stochastic resonance...
Spectrum sensing is essential in cognitive radio to enable dynamic spectrum access. In many scenarios, primary user signal must be detected reliably in low signal-to-noise ratio (SNR) regime under required sensing time. We propose to use stochastic resonance, a nonlinear filter having certain resonance frequency, to detect primary users when the SNR is very low. Both block and sequential detection...
Fully exploiting the phase and magnitude information in received data is crucial to the detection of cognitive radio signals, and this is usually done in the time domain. In fact, the same set of information can also be exploited in the frequency domain in the form of power spectrum. The most appealing one is the multitaper spectrum (MTS) estimator, which enjoys a high estimation accuracy and relatively...
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