Nonparametric Cyclic Polyspectrum-Based Spectrum Sensing

The emergence of cognitive radios and their opportunistic use of the radio spectrum calls for efficient spectrum sensing algorithms, able to reliably detect signals in very low Signal-to-Noise Ratio (SNR) environments with unknown or changing statistical distributions. Cyclic-feature detectors, which make use of the cyclostationary signature of communication signals, are a promising lead to meet these requirements. This paper presents a new nonparametric cyclic-feature detector based on the Spatial Sign Cyclic Polyspectrum (SSCP) that detects single-carrier signals for the aforementioned scenarios. In addition to being nonparametric the new detector is also robust with respect to narrowband interferers.