Selective-Reporting-Based Cooperative Spectrum Sensing Strategies for Cognitive Radio Networks

Cooperative spectrum sensing may cause a high sensing overhead to secondary users (SUs) and induce much interference to primary users (PUs) due to detection result reporting, although it can improve the detection probability. In this paper, we propose two novel selective-reporting-based cooperative spectrum sensing strategies, called random-selection reporting (RSR) and best-selection reporting (BSR), aimed at reducing the sensing overhead of SUs and limiting the induced interference to PUs. By considering the interference impact on decision reporting from PUs, we derive closed-form expressions of false-alarm probability and detection probability over Rayleigh fading channels for traditional, RSR, and BSR strategies, respectively. We also analyze the interference impact on PUs from cooperative SUs and then show that such interference can be limited by power control to satisfy a given quality-of-service (QoS) requirement of primary transmissions. Finally, numerical and simulation results reveal that the proposed strategies can remarkably reduce the sensing overhead without degrading the detection performance compared with the traditional case. Moreover, we show that both RSR and BSR can achieve minimized miss detection probability and sensing overhead by adjusting the sensing time allocation.