A weighted algorithm of spectrum sensing in cognitive radio networks

In cognitive radio networks (CRNs), the performance of spectrum sensing is the key factor that affects the system detection performance. In this paper, an optimized algorithm Weighted Spectrum Sensing with Feedback (WSSF) has been proposed, to improve sensing performance. Considering the fact that previous sensing results of secondary users (SUs) may have important implication on the current decision, these results have been taking into account in the current decision, with different weights corresponding to different sensing time. Simulation results show that the probability of detection is improved without increasing the complexity by our proposal.