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Sampling rate is the bottleneck for spectrum sensing over multi-GHz bandwidth. Recent progress in Compressed Sensing (CS) initialized several sub-Nyquist rate approaches to overcome the problem. However, efforts to design CS reconstruction algorithms for wideband spectrum sensing are very limited. It is possible to further reduce the sampling rate requirement and improve reconstruction performance via algorithms considering prior knowledge of cognitive radio spectrum usages. In this paper, the authors group the usages of cognitive radio spectrum into three categories and propose a modified Orthogonal Matching Pursuit (OMP) algorithm for wideband spectrum sensing.
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