Phase-compensation-based cooperative spectrum sensing algorithm for cognitive cloud networks

Spectrum sensing is the key technology in cognitive radio networks. In this paper, we propose novel cooperative sensing methods based on the phase compensation of signals received. In the scheme proposed, all of the signals received in secondary users (SUs) are sent to the cloud and compensated for their phase differences. After the phase compensation, the compensated signals are combined to be detected whether primary users (PUs) is present. In particular, the two phase compensation algorithms are presented. One is based on the Cosine law; the other is based on the steepest descent algorithm. It makes the cooperative spectrum sensing more accurately and efficiently. Simulation results show that the algorithms proposed provide better performance compared with other algorithms.