Spectrum opportunity detection with weak and correlated signals

We present a novel score detector for temporal spectrum opportunity detection in cognitive radio by exploiting the differences in both energy and correlation of the empty band and the occupied band. Motivated by the challenge of detecting a weak primary user´s signal without precise knowledge of the signal, where the conventional energy detector faces the limit of “SNR wall”, we assume a simple model which captures a key difference between noise and primary user´s signal - their correlation structures. Besides the merit of incorporating signal correlation, our score detector also avoids the computational complexity of covariance matrix inversion incurred by the corresponding maximum likelihood statistic assuming signal correlation. We provide a theoretical approximation to the false-alarm-rate of the score detector, which can be used to determine the threshold efficiently. We demonstrate that our approximation is quite accurate, and that our score detector has an advantage when the signal is weak and correlated.