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A Universal Multiple Antenna Test for Spectrum Sensing

We propose a general multiple antennas’ detector for spectrum sensing in cognitive radios based on complex Rao test. In contrast with conventional spectrum sensing detectors, we do not make any particular assumption for the primary user’s signal and its covariance matrix, for calculating the decision statistics. First, we derive the optimal detector by assuming complete knowledge about noise covariance matrix. Then, we consider three special structures for noise covariance matrices for cases when the variance of the noise is known and then in the calibrated and also uncalibrated antenna array, when the noise variance is unknown, and re-derive the corresponding detectors in each of these cases. Simulation results show that the performance of the proposed detectors is better than their counterparts under different practical scenarios.