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Sampling rate is the bottleneck for spectrum sensing over multi-GHzbandwidth. Recent progress in compressed sensing (CS) initialized severalsub-Nyquist rate approaches to overcome the problem. However, efforts to designCS reconstruction algorithms for wideband spectrum sensing are very limited. Itis possible to further reduce the sampling rate requirement and improvereconstruction performance via algorithms considering prior knowledge ofcognitive radio spectrum usages. In this paper, we group the usages ofcognitive radio spectrum into three categories and propose a modifiedorthogonal matching pursuit (OMP) algorithm for wideband spectrum sensing.Simulation results show that this modified OMP algorithm outperforms twomodified basis pursuit de-noising (BPDN) algorithms in terms of reconstructionperformance and computation time.

Modified Orthogonal Matching Pursuit Algorithm for Cognitive Radio Wideband Spectrum Sensing