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The speed and accuracy of spectrum sensing techniques are essential factors in the performance of cognitive radio networks. The limitations imposed by computational complexity and limited monitoring time window impede the success of spectrum sensing operation performed by cognitive radio nodes. Compressive sensing technique is viewed as a novel approach to solve scalability problems in some signal processing operations. One popular application of compressed sensing is sizable image recovery. This technique can be used in spectrum sensing applications to reduce the barriers of current spectrum sensing computational requirements. The success of this technique will result in faster sensing operations, less complex sensing modules, or wider spectrum sensing capabilities. The coming IEEE 802.22 air interface standard aims to provide wireless services in wireless regional area network using TV spectrum white spaces. This standard is considered as the first standard that is based on cognitive radio approach. Spectrum sensing is a critical functionality that needs to be performed by 802.22 compliant devices. While, the standard does not specify any spectrum sensing method, it requires the sensing operation to be performed within timing and accuracy constraints. This work in progress is investigating the feasibility of using one of the compressive sensing techniques named Fast Fourier Sampling to detect wireless microphone signals for IEEE 802.22 air interface.