An Energy Approximation Model Based on Restricted Isometry Property in Compressive Spectrum Sensing for Cognitive Radio

In recent decades, rapid growth in wireless communication service makes the limited spectrum resources become increasingly scarce. Cognitive radio [1] can solve this problem by dynamic spectrum access technology. Spectrum sensing is one of the key technology of cognitive radios and the quick and accurate perception of broadband spectrum hole is the main challenge. In order to improve the efficiency of spectrum sensing, it’s necessary to apply the wideband spectrum sensing. However the main challenge in the wideband spectrum sensing applications is the fast sampling rate which is difficult to realize by modern sampling system. Then, Compressed Sensing (CS) is proposed [2], which makes it possible to reconstruct the sparse or compressible signals from far fewer samples than Nyquist samples [3], [4] Therefore, CS can be used for wideband spectrum sensing because of the sparsity of spectrum data [5], [6].