Low complexity trace based spectrum sensing algorithms: Complex signal

In this paper, the multi-antenna spectrum sensing for complex signals are considered. The totally-blind and half-blind spectrum sensing algorithms based on the trace of the sample covariance matrix (SCM) with low computing complexity are proposed. The former can carry out spectrum sensing without prior knowledge of the noise variance, wireless channel and primary signal, and the latter only requires prior knowledge of the noise variance. The analytical expressions for the probability of false alarm and the theoretical detection thresholds for them are also presented. A performance comparison between the proposed methods and other existing methods, such as the energy detector (ED), the covariance absolute value based method, the generalized likelihood ratio test (GLRT) based method and the eigenvalue based methods, is demonstrated. Simulation results show that the new methods can produce reliable sensing results, especially the totally-blind method exhibits higher detection probability than other existing detection techniques.