  There has been a growing interest in wideband spectrum sensing due to its
applications in cognitive radios and electronic surveillance. To overcome the
sampling rate bottleneck for wideband spectrum sensing, in this paper, we study
the problem of compressed power spectrum estimation whose objective is to
reconstruct the power spectrum of a wide-sense stationary signal based on
sub-Nyquist samples. By exploring the sampling structure inherent in the
multicoset sampling scheme, we develop a computationally efficient method for
power spectrum reconstruction. An important advantage of our proposed method
over existing compressed power spectrum estimation methods is that our proposed
method, whose primary computational task consists of fast Fourier transform
(FFT), has a very low computational complexity. Such a merit makes it possible
to efficiently implement the proposed algorithm in a practical
field-programmable gate array (FPGA)-based system for real-time wideband
spectrum sensing. Our proposed method also provides a new perspective on the
power spectrum recovery condition, which leads to a result similar to what was
reported in prior works. Simulation results are presented to show the
computational efficiency and the effectiveness of the proposed method.
