Abstract
The most challenging problem in Cognitive radio is the detection of unused frequency bands and exploit them opportunistically for spectrum access. Cognitive radios must be able to efficiently detect the primary users even in low signal-to-noise ratio (SNR) condition and in fading environments. These difficulties can be overcome by exploiting the cyclostationary signatures exhibited by communications signal. Cyclostationary signatures are embedded in the physical properties of communications signal and they can be used to distinguish between the primary user and secondary user. In this paper, we investigate the problem of detecting vacant spectral bands using cyclostationary feature extraction method. Approaches for the detection of cyclostationary signatures are outlined and the simulation results are presented.
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