Open AccessSubsampled Circulant Matrix Based Wideband Spectrum Sensing Using Fusion Based Recovery Algorithm
Author(s) -
T. V. N. L. Aswini,
K. Padma Raju,
Leela B. Kumari
Publication year - 2021
Publication title -
traitement du signal/ts. traitement du signal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.279
H-Index - 11
eISSN - 1958-5608
pISSN - 0765-0019
DOI - 10.18280/ts.380431
Subject(s) - wideband , compressed sensing , cognitive radio , circulant matrix , nyquist–shannon sampling theorem , computer science , algorithm , spectrum (functional analysis) , matrix (chemical analysis) , wireless , electronic engineering , telecommunications , engineering , computer vision , physics , materials science , quantum mechanics , composite material
This paper reflects the problem of wideband spectrum recovery. The demand for spectrum usage is increasing exponentially as the wireless technologies rules the world. To meet these needs, Cognitive Radio is one of the emerging technologies, which intelligently allots the spectrum to the secondary users. Since the spectrum is wideband, the capability of spectrum sensing is improved by introducing sub-nyquist sampling under compressive sensing framework. In this paper, a sub-nyquist sampling technique of Modulated Wideband Converter (MWC) is used as it possesses m-parallel channels providing fast sensing and robust structure. A circulant matrix method is used to improve the hardware complexity of MWC. Also at the reconstruction of MWC, a fusion based recovery algorithm is proposed which became an added benefit for perfect recovery of the support. The results are compared with conventional MWC in terms of support recovery, mean square error and SNR gain. Simulations proved that the proposed algorithm performs superior at low as well as high SNR with increased gain.