Fast Compressed Power Spectrum Estimation: Toward a Practical Solution for Wideband Spectrum Sensing

Abstract

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.Index Terms-Compressed sampling, wideband spectrum sensing, power spectrum estimation.

Compressive Sensing Approach to Harmonics Detection in the Ship Electrical Network

“…CS is widely used in diverse fields, e.g., biomedical applications, communication systems, and pattern recognition, as well as electrical PQ estimation [15,16]. Various new techniques for identifying and estimating harmonic sources in electricity supply systems have been presented in the literature [17][18][19][20][21][22][23][24][25][26][27][28]. The papers [17][18][19][20][21] concern the distributed monitoring of harmonic and interharmonic pollution in electrical power delivery systems.…”

“…In order to reduce implementation costs, the authors propose a distributed architecture, based on cost-effective nodes that use the CS strategy. Some papers [22][23][24][25][26][27][28] consider the different methods of compressive sampling and innovative CS algorithms for reconstruction of the PQ interference signal.…”

A Modulated Wideband Converter Calibration Technique Based on a Single Measurement of a White Noise Signal with Advanced Resynchronization Preprocessing

“…Several techniques, depending or not on the knowledge of the carrier frequency, have been developed to monitor a multiband spectrum (random demodulator [4,5], multicoset sampling [6,7], Modulated Wideband Converter [8], quadrature analog-to-information converter [9], time-segmented quadrature analog-to-information converter [10], random triggering based modulated wideband compressive sampling [11] and non uniform wavelet sampling [12,13]). In the case of known carrier frequencies, a band of interest is firstly chosen and the signal is demodulated by its carrier frequency.…”

Compressive Wideband Spectrum Sensing and Carrier Frequency Estimation with Unknown Mimo Channels

“…Besides, the nonlinear sparse signal recovery algorithms usually involve a high computational complexity that may be excessive for practical systems. Another line of research [11][12][13][14][15][16] is to directly reconstruct the power spectrum from sub-Nyquist data samples. This class of approach, due to the exploitation of statistical information, can provide reliable spectrum sensing in low SNR environments.…”