Polarization Spectrum Sensing Exploiting Eigenvalue based Goodness-of-Fit Detection

Spectrum sensing is the significant technology for cognitive radio and spectrum monitoring. In this paper, a polarization spectrum sensing method based on eigenvalue based goodness-of-fit test is studied. The wireless communication system are deployed by dual polarization antennas, i.e., the horizontal polarization and the vertical polarization. For the received signal in dual polarization antennas, we use three eigenvalues of the sample covariance matrix as the observation samples of GoF, i.e., the maximum eigenvalue, the ratio of maximum eigenvalue to trace, the maximum to minimum eigenvalue. The simulation compared the studied algorithms in terms of the detection performance. The results show that the detection performance are different in low and high signal to noise ratio. Polarization channel is harmful only in low signal to noise ratio.