A Blind Spatial Spectrum Sensing Algorithm Based On Weighted Music

State-of-the-art sensing methods only exploit three dimensions of the spectrum space: frequency, time and geography whereas the angle dimension, that is, spatial spectrum sensing has not been exploited well enough. In this paper, we apply the multiple signal classification (MUSIC) Angle of Arrival (AoA) estimation method into spectrum sensing. Note that MUSIC method needs to know the number of signals, which is not available in sensing scenario. Hence, we use eigenvalue weighting scheme to design an improved MUSIC method which does not need the number of arriving signals. Utilizing the maximum-minimum spectrum ratio of the improved MUSIC method, we finally propose a blind weighted MUSIC based detection algorithm. Taking the advantage of the high peak and resolution of MUSIC method, the proposed method can achieve high probability of detection as well as offer the AOA information for spectrum access, which improve the spectrum efficiency. Simulation results are presented to verify the efficiency of the proposed algorithm.