Wideband spectrum sensing for cognitive radios in unknown noise via power spectrum analysis

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). We propose two spectrum sensing methods based on comparing the power spectral densities estimated from data acquired over two non-overlapping time segments. The first window serves as a reference for noise and interference while the second window may or may not contain primary user(s). Two binary hypothesis tests based on the generalized likelihood ratio test (GLRT) paradigm are formulated for comparing the power spectra estimated from the two time segments. Illustrative simulation examples are presented.