Abstract
In this paper, Compressed Sensing (CS) is introduced to wideband spectrum sensing for cognitive radio to deal with the too high sampling rate challenge. The standard sparse signal recovery of CS does not consider the distortion in the Analogue-to-Information Converter (AIC). Thus we define a new sparse signal model with bounded sampling error, and an Anti-Sampling-Distortion Constraint (ASDC) is deduced. We combine the L1-norm based sparse constraint with the ASDC to get a novel robust sparse signal recovery operator. Numerical simulations demonstrate that the proposed method outperforms standard sparse wideband spectrum sensing in accuracy, denoising ability, etc.
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