Wideband Spectrum Sensing Scheme in Cognitive Radio Networks with Multiple Primary Networks

Spectrum sensing is one of the key issues for spectrum sharing in cognitive radio networks to deal with the more and more serious problem on exhaustive spectrum resource. In this paper, we study the problem of wideband spectrum sensing in cognitive radio networks with multiple primary networks. By dividing the total wideband spectrum into many groups with relatively small number of narrowbands, a novel wideband spectrum sensing scheme is proposed. In the proposed scheme, the number and corresponding probability of free bands in each group are predicted by Lempel-Ziv based prediction algorithm. Then the optimal number of secondary users that will sense the narrowbands in each group is found to maximize the defined reward. Not only the sensing speed and accuracy but also the system reward are improved in this paper. Finally, extensive simulation results are provided to show the effectiveness of our proposed wideband spectrum sensing scheme by comparing with the existing ones.