Autocorrelation-based multiantenna spectrum sensing in colored noise

One of the first steps to be accomplished by a cognitive user in cognitive radio applications is spectrum sensing: analysis of the received electromagnetic transmissions to search for unoccupied spectrum bands (spectrum holes). Recently several time-domain approaches relying on the generalized likelihood ratio test (GLRT) paradigm have been proposed for multiple antenna spectrum sensing in cognitive radios. These approaches are suitable for flat-fading channels in white noise with equal noise variances across antennas; knowledge of the noise variance is not required, unlike the energy detector. In this paper we investigate a method based on the sample autocorrelation of the received multiantenna signal where we allow the noise to be colored and its variances to be different at different antennas without requiring knowledge of their spectra. Supporting simulation examples are provided.