Low complexity spectrum sensing algorithm robust to noise uncertainty

Robust spectrum sensing is a fundamental component in cognitive radio due to the noise uncertainty. In this paper, we propose a robust spectrum sensing algorithm based on the covariance matrix of signals received at the secondary users. The proposed method can even perform better than the ideal energy detection even if the received signals are highly correlated. The test statistic used in the algorithm is dependent on mean and standard deviation of eigenvalues and can be calculated from the trace of covariance matrix and trace of square of the covariance matrix. Simulations verifying the robustness and performance of the proposed algorithm are presented.