Robust spectrum sensing method based on ranks over non-Gaussian channels

Robust spectrum sensing is well-known to combat noise model variations and uncertainties. Detection based on signs and ranks of the received samples are more robust against model variations when there is no pre-know of the channel parameters. Here, we propose a two-sample distribution-free test based on rank summation of received signal which is compared to the other eminent methods like Energy Detection (ED) and robust Nonparametric Cyclostationaity-based Detection (NPCSD). The results show that the proposed method outperforms the aforementioned detection methods in the presence of non-Gaussian noise. However, the proposed method in spite of conventional methods, does not require any a-priori statistical information about noise model.