@conference {685, title = {Compressive wideband spectrum sensing with spectral prior information}, booktitle = {Int. Conf. Acoust., Speech, Signal Process. (ICASSP)}, year = {2013}, abstract = {
Wideband spectrum sensing provides a means to determine
the occupancy of channels spanning a broad range of frequencies.
Practical limitations impose that the acquisition should
be accomplished at a low rate, much below the Nyquist lower
bound. Dramatic rate reductions can be obtained by the observation
that only a few parameters need to be estimated in
typical spectrum sensing applications. This paper discusses
the joint estimation of the power of a number of channels,
whose power spectral density (PSD) is known up to a scale
factor, using compressive measurements. First, relying on
a Gaussian assumption, an efficient approximate maximum
likelihood (ML) technique is presented. Next, a least-squares
estimator is applied for the general non-Gaussian case.
}, keywords = {cognitive radio, dynacs, spectrum sensing}, doi = {10.1109/ICASSP.2013.6638505}, author = {Daniel Romero and R. L{\'o}pez-Valcarce and Geert Leus} }