Cooperative Spectrum Sensing Based on Blind Source Separation for Cognitive Radio

In currently cooperative spectrum sensing, each secondary user requires some information in order to achieve the vacant spectrum sensing. Energy detection is commonly used in local spectrum sensing. However, performance of cooperative spectrum sensing based on energy detection is damaged due to the noise uncertainty in realistic environment. In this paper, blind source separation algorithm is introduced to spectrum sensing for cognitive radio. Therefore local blind spectrum sensing is proposed, which is based on source separation. Blind spectrum sensing does not require any information of the source signal and the channel. So it can accomplish local spectrum sensing on total blind. Further, because of the advantage of blind spectrum sensing, we can exploit it to cooperative spectrum sensing. And cooperative spectrum sensing based on blind source separation is given, which can improve reliability of cooperative spectrum sensing. Numerical analysis and computer simulation suggest that proposed algorithm achieves the vacant spectrum sensing and overcomes effect of noise uncertainty to statistical decision. Moreover, blind spectrum sensing should be better than energy detection for correlated signals.