A robust spectrum sensing scheme based on multiple antennas for cognitive radios

In this paper, we investigate a robust spectrum sensing scheme using multiple antennas, which exploits the information of eigenvalues´ characteristics of the sample covariance matrix. The difference between the maximum eigenvalue and the average of the remainder eigenvalues of sample covariance matrix is utilized as the test statistic. Besides, by exploiting Gaussian approximation for the test statistic, the closed-form expression of the decision threshold is derived in accordance with Neyman-Pearson criterion. The proposed scheme can perform well without any prior knowledge of primary signal and fading channels. Moreover, extensive numerical results show that the proposed scheme is invulnerable to the noise uncertainty, and can achieve better detection performance than the other existing methods.