Multiple Subspace Matching Pursuit for spectrum Sensing

초록

Spectrum sensing is used to perceive the spectral environment over a wide frequency band. The multiple measurement vector (MMV) model can be applied to the spectrum sensing scenario since it enables jointly sparse signal recovery. In this paper, a novel spectrum sensing algorithm, referred to as multiple subspace matching pursuit (MSMP), is proposed to reduce the miss detection and false alarm events in the spectrum sensing. Numerical simulations demonstrate that the proposed algorithm shows the outstanding recovery performance with the reduction of the incorrect spectrum decisions.