Covariance matrix based spectrum sensing for OFDM based cognitive radio

Spectrum sensing is a key technology for the cognitive radio. Since orthogonal frequency-division multiplexing (OFDM) is one of the major wideband transmission techniques, spectrum sensing for OFDM based primary signals using its sample covariance matrix is developed. In this paper, two sensing methods based the sample covariance matrix are proposed: one is based on testing hypothesis in which the covariance matrix is assumed to equal to a unit matrix hypothesis and the other is based on the ratio of the maximum eigenvalue to minimum eigenvalue of the sample covariance matrix. The performance of the method is validated by simulations. A comparison of this method with cyclic prefix (CP) correlation coefficient (CPCC) is also carried out.