Cooperative Spectrum Sensing Based on Generalized Likelihood Ratio Test for Cognitive Radio Channels with Unknown Primary User's Power and Colored Noise

Background & Objective: This paper proposes a modified eigenvalue-based Generalized Likelihood Ratio Test (GLRT). The proposed model is appropriate for cognitive wireless radio system under colored noise and unknown primary user's power. Herein, we introduce an optimization problem, which maximizes the detection probability under the constraints of false alarm, sensing time, the weighting of eigenvalues, and Energy Efficiency (EE). In addition, we improve the detection probability by achieving the proper number of cooperative secondary users using the power method. Conclusion: Simulation results show that the computational complexity of the proposed method is lower than that for traditional methods, Energy Detection (ED) and Eigenvalue-Based (EVB).