Spectrum sensing based on GoF testing techniques

In this paper, goodness-of-fit (GoF)-based spectrum sensing problem is investigated for detection of orthogonal frequency-division multiplexing (OFDM) signals. In essence, some novel local sensing approaches based on Shapiro-Wilk (SW), Shapiro-Francia (SF), lilliefors (LI), and Jarque-Bera (JB) tests are offered. Then, we propose a mixed approach based on SW and SF tests. These methods do not require any prior information about the primary signals. In addition, the order of computational complexity of the offered methods is computed and demonstrated that proposed methods have less complexity order and fast performance in comparison with the AndersonDarling method. Finally, the detection performance of the proposed methods is evaluated through simulations. The results demonstrate the superiority of the mixed method.