Dynamic Adaptive Double-threshold Cooperative Spectrum Sensing with Multi-level Quantization

In this paper, a dynamic adaptive double-threshold cooperative spectrum sensing scheme considering multi- level quantization is proposed to reduce the system overhead and improve the reliability of global decision. The proposed scheme that combining hard fusion and soft fusion is able to dynamically adjust the double-threshold according to the channel situation. The multi- level quantization method is adopted in the uncertain region of the traditional double-threshold energy detection to solve the problem that the sensing information is ignored between the two determined thresholds. Then the optimization problem about the minimized error detection probability is analyzed, based on which a closed-form expression for the optimal decision threshold is analytically derived. Simulation results show that the detection performance of this method is better than hard decision rules and closed to traditional soft fusion rules, and has lower collaborative cost.