Two-Round Cooperation Based Spectrum Sensing in Cognitive Radio Networks

Cooperative spectrum sensing is a fast and effective approach to improve sensing performance in cognitive radio networks. However, in order to reduce the bandwidth demands of cooperation, censoring is needed. In this paper, we propose a Two-Round Cooperation based Spectrum Sensing algorithm (TRCSS) according to local three-threshold decision results. More specifically, after the first round censoring failed, cognitive users begin to report the second local decision bits to fusion center to proceed the second round cooperation, thus sensing failure is eliminated. Furthermore, integrating uncertainty of noise variance, we propose a simple method to set local decision threshold values. Numerical results show that TRCSS algorithm does not significantly increase the number of sensing bits, especially with much cooperative users. In addition, the complementary ROC curves demonstrate that the TRCSS algorithm is superior to the conventional double-threshold sensing methods in performance.