Blind Spectrum Sensing Based on Cyclostationary Feature Detection
Cognitive Radio has emerged as a promising technology to improve the spectrum utilization efficiency, where spectrum sensing is the key functionality to enable its deployment. This study proposes a cyclostationary feature detection method for signals with unknown parameters. We develop a rule of automatic decision based on the resulting hypothesis test and without statistical knowledge of the communication channel. Performance analysis and simulation results indicate that the obtained algorithm outperforms reported solutions under low SNR regime.
KeywordsCognitive radio Cyclostationarity Feature detection Blind spectrum sensing
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