Spectrum sensing is of great importance in the cognitive radio (CR) networks.\nCompared with individual spectrum sensing, cooperative spectrum sensing (CSS) has been shown to\ngreatly improve the accuracy of the detection. However, the existing CSS algorithms are sensitive\nto noise uncertainty and are inaccurate in low signal-to-noise ratio (SNR) detection. To address\nthis, we propose a double-threshold CSS algorithm based on Sevcik fractal dimension (SFD) in\nthis paper. The main idea of the presented scheme is to sense the presence of primary users in\nthe local spectrum sensing by analyzing different characteristics of the SFD between signals and\nnoise. Considering the stochastic fluctuation characteristic of the noise SFD in a certain range, we\nadopt the double-threshold method in the multi-cognitive user CSS so as to improve the detection\naccuracy, where thresholds are set according to the maximum and minimum values of the noise SFD.\nAfter obtaining the detection results, the cognitive user sends local detection results to the fusion\ncenter for reliability fusion. Simulation results demonstrate that the proposed method is insensitive\nto noise uncertainty. Simulations also show that the algorithm presented in this paper can achieve\nhigh detection performance at the low SNR region.
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