TY - JOUR
T1 - Fast Compressed Power Spectrum Estimation
T2 - Toward a Practical Solution for Wideband Spectrum Sensing
AU - Yang, Linxiao
AU - Fang, Jun
AU - Duan, Huiping
AU - Li, Hongbin
N1 - Publisher Copyright:
© 2002-2012 IEEE.
PY - 2020/1
Y1 - 2020/1
N2 - 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.
AB - 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.
KW - Compressed sampling
KW - power spectrum estimation
KW - wideband spectrum sensing
UR - http://www.scopus.com/inward/record.url?scp=85078338756&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85078338756&partnerID=8YFLogxK
U2 - 10.1109/TWC.2019.2946805
DO - 10.1109/TWC.2019.2946805
M3 - Article
AN - SCOPUS:85078338756
SN - 1536-1276
VL - 19
SP - 520
EP - 532
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
IS - 1
M1 - 8874996
ER -