A novel spectrum sensing algorithm for small-scale primary users detection

A novel goodness-of-fit testing based spectrum sensing method is proposed to detect the small-scale primary users (SSPUs) such as wireless microphones and mobile devices. In the proposed method, a secondary user (SU) measures the non-Gaussianity of the spectrum of the received signal using a novel test statistic. Then, the absence and presence of SSPUs can be effectively distinguished by evaluate how well the spectrum distribution of the received signal mismatch that of the noise signal. Since the decision threshold of the proposed algorithm is independent on any priory knowledge of SSPUs and noise, our method is blind and more robust to the uncertain noise than some existing spectrum sensing algorithms. Moreover, the proposed method can obtain a significant spectrum detection performance even under low signal-to-noise ratio.