Capacity-Aware Cooperative Spectrum Sensing Based on Noise Power Estimation

Most cooperative spectrum sensing research activities focus on maximizing the primary user detection and neglect the achieved secondary system performance. This paper proposes a novel capacity-aware cooperative spectrum sensing optimization method, capable of computing the optimal values for the cooperative sensing parameters (e.g., the number of sensed samples, the number of cooperating devices, control channel bandwidth) so that the secondary system capacity is maximized. The proposed method utilizes energy detection with estimated noise power (ENP). We derive and experimentally validate the analytical models for cooperative spectrum sensing based on the ENP method. Additionally, we evaluate the performance of the proposed capacity-aware spectrum sensing described in this paper. We show that the proposed capacity-aware cooperative spectrum sensing based on noise power estimation achieves enhanced secondary system capacity compared to the previous commonly proposed sensing processes that maximize the detection performance. Moreover, the results give insight into the optimal behavior of the proposed capacity-aware cooperative spectrum sensing based on noise power estimation regarding the common cooperative spectrum sensing parameters.