Sensing Confidence Level-Based Cooperative Spectrum Sensing Algorithm

Cooperative spectrum sensing is a key technology to tackle the challenges such as fading or hidden terminal problem in local spectrum sensing of cognitive radio system. Conventional cooperative method could improve the detection performance in some sense, but increase overhead of control channel. In order to reduce the overhead, a new cooperative spectrum sensing algorithm based on confidence level was proposed. In this algorithm, the maximum-eigenvalue-based detection scheme was carried out to obtain the local spectrum detection. The detection probability and false alarm probability of each secondary user are used to estimate the reliability of the sensing decision. The test statistic of the secondary users with high reliability are chosen and sent to fusion center. Then weighted factors of chosen secondary user´s are derived from the creditability values, and the global decision is made by weighted fusion at fusion center. The simulation results showed that the proposed algorithm improves the detection probability in the guarantee of the false-alarm probability close to 0 and saves half of the overhead in the control channel.