Rapid Polarization Adaptation Based Spectrum Sensing Algorithm for Cognitive Radios

To utilize the polarization state of primary signal which is the crucial vector characteristic for spectrum sensing, a rapid polarization adaptation algorithm is proposed based on the K-armed bandit. The proposed algorithm can reduce the complexity and converge rapidly by transferring the two-degree-of-freedom search issue to K single-dimensional issues, and identify the polarization state of primary signal to realize real-time spectrum sensing for Cognitive Radios (CR). Further, the theoretical boundary of the proposed algorithm is derived. The spectrum sensing performance on the basis of the polarization state identification is discussed by receiver operation characteristic curve finally. The simulation results show that the proposed algorithm converges fast, and obtains a high accuracy on polarization state identification for primary signal. The detection performance is more effective with the rapid polarization adaptation.