Abstract
Spectrum sensing is one of the key challenges in the cognitive radio network. Primary user signal must be detected reliably in the low signal-to-noise ratio (SNR) regime and in multipath fading environments. This paper analyzes effects of time-variant multipath Rayleigh fading channel on cyclostationary characteristics and derives the relationship between cyclostationary statistics of transmitted and received signal. Depending on the distinct feature and the set of tested cyclic frequencies, the test statistics may have different performances. Cyclostationary features of small scale should be selected to be detected taking multipath effects into account. A novel solution to detect cyclostationary features combining time and frequency domain is proposed. Simulation results illustrating the reliability of solution as well as the effects of time-variant multipath fading channel on features are presented.
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