Wideband spectrum sensing in cognitive radio with structured Bayesian compressed sensing by variational Bayesian approach

摘要

Due to the poor spectrum utilization in time and space, the spectrum in cognitive radio is not only sparse but clusters in blocks in many situations. Based on the fact, a novel Bayesian compressed sensing algorithm for wideband spectrum sensing is proposed. In our proposed framework, firstly, the original signal should be sampled with sub-Nyquist sampling rate. Secondly, the clustering of the spectrum molded by many block structures is also utilized to increase the accuracy of spectrum sensing. Lastly, with a variational Bayesian inference, the experimental results show the validity and advantage of our proposed approach.