Spectrum Sensing for Cognitive Radios over Frequency Selective Channels in White Noise

Cognitive radio allows for usage of licensed frequency bands by unlicensed users when the licensed spectrum bands are unoccupied. Therefore, one of the first critical steps to be accomplished by a cognitive user is spectrum sensing: search for unoccupied spectrum bands (spectrum holes). A popular approach is that of energy detection whose implementation requires accurate knowledge of noise power. The performance of the energy detector deteriorates rapidly in the presence of noise power uncertainty. Recently several time-domain approaches relying on the generalized likelihood ratio test (GLRT) paradigm have been proposed for multiple antenna spectrum sensing which obviate the need for the knowledge of the noise variance, unlike the energy detector. That is, multiple antennas at the receivers are needed to tackle the problem of unknown noise power. In this paper we investigate a single-antenna method for signal detection in white noise based on analysis of the power spectral density (PSD) of the received signal relying on the bandlimited nature of the signal to be detected. Our proposed approach is also based on GLRT but exploits the fact that while noise is white, the signal is colored; it does not require knowledge of the noise power. Simulation examples are provided in support of the proposed approach.