A Cooperative Spectrum Sensing Algorithm Based on Fuzzy Credibility

Due to multipath fading and shadow effect etc factors, single cognitive user can’t distinguish between the unused bands and license user’s signal in deep fade. Cooperative spectrum sensing uses information fusion technology to improve spectrum sensing performance by combining multi-cognitive users sensing results. Theory of evidence is an effective way of uncertainty reasoning, which has been used in cooperative spectrum sensing well. In this paper it integrates fuzzy set with theory of evidence and puts forward a cooperative spectrum sensing algorithm based on fuzzy credibility. Each cognitive user first makes local energy detection. Then it uses normal-shaped membership function as basic probability assignment which assigns credibility by cognitive user’s detection result. The fusion center receives all cognitive users’ evidence and combines them by Dempster rule. At last the fusion center draws a conclusion. As simulation results shown, the cooperative spectrum sensing algorithm based on fuzzy credibility has a better sensing performance or algorithm complexity than existing cooperative spectrum sensing algorithm based on theory of evidence.