Satellite-based Multi-Resolution Compressive Spectrum Detection in Cognitive Radio Networks

The cognitive radio technology is considered as a suitable way to improve the utilization of the radio spectrum and a promising solution to solve the coexistence problem of two wireless networks operating on the same frequency band. In this paper, a satellite-based multi-resolution compressive spectrum detection algorithm is proposed to help the coexistence of a mobile satellite system and an infrastructured wireless terrestrial network. With the help of compressive sensing techniques, sub-Nyquist rate samples are acquired, and utilized to detect frequency subbands via a wavelet-based edge detector. Then a double-threshold energy detector is used to realize the multi-resolution spectrum detection. Simulation results show that at sub-Nyquist rates, the proposed algorithm has near-optimal detection performance without sensing the whole band at the maximum resolution.