Optimal user selection algorithm based cooperative spectrum sensing for cognitive radio

Gerschgorin disk theorem based optimal user selection algorithm is proposed for cooperative spectrum sensing. The fusion center receives the sensing data from the secondary users and establishes the optimal user selection mechanism by employing Gerschgorin disk theorem. The sensing data of the selected secondary users will subsequently be fused as the global test statistic. Aided by the optimal user selection strategy, the cooperative sensing performance can be ameliorated. Furthermore, the detection performance can also be improved through the proposed iterative thresholding algorithm. Theoretical analysis and simulation results show that the algorithm depends on no a priori knowledge of the primary user signal and the noise power. The proposed method is hence robust against the noise power uncertainty, and can maintain consistent performance when slightly fewer sampling data and users are involved in cooperative sensing.