Wideband Power Spectrum Sensing: A Fast Practical Solution for Nyquist Folding Receiver

The limited availability of spectrum resources has been growing into a critical problem in wireless communications, remote sensing, and electronic surveillance, etc. To address the high-speed sampling bottleneck of wideband spectrum sensing, a fast and practical solution of power spectrum estimation for Nyquist folding receiver (NYFR) is proposed in this article. The NYFR architecture can theoretically achieve full-band signal sensing with a hundred percent probability of intercept. However, the existing algorithm is difficult to realize in real-time due to its high complexity and complicated calculations. By exploring the subsampling principle inherent in NYFR, a computationally efficient method is introduced with compressive covariance sensing. That can be efficiently implemented via only the nonuniform fast Fourier transform, fast Fourier transform, and some simple multiplication operations. Meanwhile, the state-of-the-art power spectrum reconstruction model for NYFR of time-domain and frequency-domain is constructed in this article as a comparison. Furthermore, the computational complexity of the proposed method scales linearly with the Nyquist-rate sampled number of samples and the sparsity of spectrum occupancy. Simulation results and discussion demonstrate that the low complexity in sampling and computation is a more practical solution to meet real-time wideband spectrum sensing applications. The proposed fast power spectrum sensing method for NYFR enables an increase in precision from
$10^{-3}$
to
$10^{-4}$
and a decrease in execution time from
$10^{-1}$
to
$10^{-3}$
s.