Wideband spectrum sensing technique based on multitask compressive sensing

摘要

Sensing the spectrum is the central operation to enable cognitive users to identify the spectrum occupancy. Wideband spectrum sensing enables detecting occupancy at different bands. In this paper, we propose a wavelet based multitask compressive sensing (WMCS) algorithm for constructing the spectrum edges directly from the compressive measurement. The WMCS algorithm forms new compressive sensing (CS) tasks by using the wavelet transform of the power spectral density at different scales. The algorithm then forms the spectrum subbands using the estimated edges and classifies the subbands as either occupied or sparse. Simulation results show the improved performance of the proposed algorithm.