Cooperative spectrum sensing based on a low-complexity cyclostationary detection method for cognitive radio networks

Abstract

Fast reliable spectrum sensing (SS) is a crucial problem in the cognitive radio systems. To address this issue, cyclostationarity-based detection methods, which are generally more complex but more reliable than energy detection methods, have been proposed. This paper presents a new method to detect the presence of the second-order cyclostationarity in the OFDM-based primary user (PU) signals. The proposed method has a low computational complexity, while it presents a close performance as compared to the well-known GLRT-based Dandawaté-Giannakis's method. Moreover, since the proposed low-complexity method is robust against the noise uncertainty, it can be a good alternative to the energy detection method. In order to be able to perform the hypothesis test, we derive the asymptotic distribution of the test statistic under the null hypothesis. We further propose some cooperative spectrum sensing methods to improve the detection performance. An approximate threshold selection method is proposed for performing statistical test at the fusion center (FC). Extensive simulation results confirms the superiority of the proposed schemes.