  In this paper, we propose a feature-based method for spectrum sensing of OFDM
signals from sub-Nyquist samples over a single band. We exploit the structure
of the covariance matrix of OFDM signals to convert an underdetermined set of
covariance-based equations to an overdetermined one. The statistical properties
of sample covariance matrix are analyzed and then based on that an approximate
Generalized Likelihood Ratio Test (GLRT) for detection of OFDM signals from
sub-Nyquist samples is derived. The method is also extended to the
frequency-selective channels.
