Cognitive Radio, Cooperative Spectrum Sensing Technology Research

The cognitive radio technology is a new milestone in the history of radio development. It has been recognized as an effective solution to the contradiction between the scarcity of spectrum resources and fixed spectrum allocation policy. In cognitive radio networks, cognitive users need to continuously monitor the spectrum of primary users. Spectrum sensing become the prerequisite and foundation of the cognitive radio technology. Due to shadowing and multi-path fading, single terminal detection is no so reliable and accurate. This paper mainly studies the cooperation spectrum sensing in cognitive radio.First, the paper analysis and outline the traditional single user detection methods, such as energy detection, matched filter detection and cyclostationary feature detection. Single user local detection can not meet the requirements of reliability and fast. Cooperation detection can improve the overall detection performance of cognitive networks. But cooperation increases the technical difficulty and computational complexity. Then, the paper analysis the cooperative spectrum sensing technology based on amplify and forward protocol and establish the cooperative network model of two cognitive users. Through cooperation between the two cognitive users can reduce the uncertainty of single user detecting caused by shadowing and multi-path fading. And cooperation can reduce the detection time and increasing their agility. The emulation show that cooperative spectrum sensing technology can increases the detection probability of cognitive users to primary users effectively, have more reliable detection performance. Last, studies a kind of cooperative spectrum sensing technique of equal gain combining based on data fusion. And compares the cooperative sensing method based on weighted fusion and the traditional single user energy detection and OR criteria detection. The emulation show that the overall detection performance of cooperative sensing method based on weighted fusion are much better than the traditional single user energy detection and OR criteria detection.