Robust Spectrum Sensing for Cognitive Radio with Impulsive Noise

Spectrum sensing plays an important role in cognitive radio. In this paper, a robust spectrum sensing method via empirical characteristic function based on goodness-of-fit testing is proposed, named as ECF detector. The test statistic is derived from the empirical characteristic function of the observed samples, thus the secondary users do not require any prior knowledge of the primary signal and the noise distribution. Extensive simulations are performed and compared with the existing spectrum sensing methods, such as energy detector, eigenvalue-based detector, AD detector and KS detector. The results show that, the proposed ECF detector can offer superior detection performance under both the Gaussian noise and the impulsive noise environments.