Time Agility Optimization for Dual-stage Collaborative Spectrum Sensing

Cooperative spectrum sensing has been shown to be an effective method to mitigate the impact of hidden terminal and shadow fading in cognitive radio networks. Currently most works focused on either cooperative sensing or sensing scheduling as a viable means to improve the detection performance without studying their interactions. This paper proposed a dynamic and variable time-division multiple-access scheduling mechanism that was incorporated into a Dual-stage collaborative spectrum sensing (DCSS) model in a less ideal radio environment. Moreover, this paper derived closed-form expressions of sensing time for DCSS, and addressed the critical range of timeslot length. An optimized algorithm to minimize sensing time was deduced and verified. The simulation results indicate that average sensing time with DCSS is shortened by 11.5% when compared with that of the Single collaborative spectrum sensing (SCSS) while guaranteeing detection error rate requirement of less than 1%.