Weighted average consensus based distributed compressive spectrum sensing using prior parameter exchange

In the existing distributed cooperative spectrum sensing schemes, cooperation based on consensus algorithms is a research hotspot. However, the existing methods haven´t embodied the reliability difference among cognitive radio users, so there is an enormous scope to improve the accuracy. In this paper, we propose a weighted average consensus-based distributed compressive spectrum sensing (PE-WDCS) using prior parameter exchange. In this scheme, every secondary user (SU) recovers its local wideband signal with bayesian compressive sensing method, and then conducts information fusion with proposed weighted average consensus algorithm and finally obtains the wideband signal. Simulation results show that proposed algorithm has a significant improvement compared with the existing approaches in the accuracy of wideband spectrum sensing.