This paper develops a new robust cyclostationary detection technique for spectrum sensing of OFDM-based primary users (PUs). To do so, an asymptotically constant false alarm rate (CFAR) multi-cycle detector is proposed and its statistical behavior under null hypothesis is investigated. Furthermore, to achieve higher detection capability, a soft decision fusion rule for performing cooperative spectrum sensing (CSS) in secondary networks is established. The proposed CSS scheme aims to maximize the deflection criterion at the fusion center (FC), while the reporting channels are under Rayleigh fading. In order to be able to evaluate the performance of the cooperative detector, some analytic threshold approximation methods are provided for the cases where the FC has direct sensing capability or not. Through numerical simulations, the proposed local and CSS schemes are shown to significantly enhance CR network performance in terms of detection probability metric. Manuscript profile

Goodness-of-Fit (GoF) based spectrum sensing of orthogonal frequency-division multiplexing (OFDM) signals is investigated in this paper. To this end, some novel local sensing methods based on Shapiro-Wilk (SW), Shapiro-Francia (SF), and Jarque-Bera (JB) tests are first studied. In essence, a new threshold selection technique is proposed for SF and SW tests. Then, three studied methods are applied to spectrum sensing for the first time and their performance are analyzed. Furthermore, the computational complexity of the above methods is computed and compared to each other. Simulation results demonstrate that the SF detector outperforms other existing GoF-based methods over AWGN channels. Furthermore simulation results demonstrate the superiority of the proposed SF method in additive colored Gaussian noise channels and over fading channel in comparison with the conventional energy detector. Manuscript profile