Efficient Cooperative Spectrum Sensing with Minimum Overhead in Cognitive Radio

Abstract

This letter studies cooperative spectrum sensing (CSS) in which secondary users efficiently cooperate to achieve superior detection accuracy with minimum cooperation overhead. We consider each cooperative user only spends "1 bit" on reporting its own sensing decision to data fusion center as the total cooperation overhead. However, this "1 bit" CSS could not gain better sensing outcomes in current data fusion rules (DFRs). To ameliorate this issue, we derive theorems to reveal the optimum threshold of general DFR. Then we propose three novel DFRs and related three algorithms to efficiently obtain the optimum decision threshold for different objectives. By simulations, the proposed DFRs indicate evident improvement on CSS performance.