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One of the fundamental components in Cognitive Radios (CRs) is spectrum sensing. For sensing the wide range of frequency bands, CRs need high sampling rate Analog to Digital Converters (ADCs) which have to operate at or above the Nyquist rate. The high operating rate constitutes a major implementation challenge. Compressive Sensing (CS) is a method that may overcome this problem. Sub-Nyquist rate can be used for CS recovery algorithms such as L1-minimization. While boundary information of all frequency sub-bands is available, a more efficient recovery algorithm based on L2/L1-minimization can be used instead of L1-minimization.
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