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A Low Complexity Sensing Algorithm for Wideband Sparse Spectra
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DOI：10.1109/LCOMM.2016.2616471.png)
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Abstract
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Compressed sensing-based wideband spectrum sensing approaches have gotten much attention owning to their advantage of relieving the pressure on high signal acquisition costs. Most of these approaches need to recover the signal or power spectrum, which require high computational complexity. This letter proposes a novel wideband sensing algorithm with no recovery (NoR) of spectral, where the location of occupied subband is identified via a maximum inner product method, thus reducing computational complexity significantly. Compared with the existing spectral recovery algorithms, NoR algorithm maintains an excellent sensing performance with several orders of magnitude lower computational complexity.
Keywords:
Wideband spectrum sensing
sparse spectral
folded spectrum
subband classification
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