Performance of Blind Cooperative Spectrum Sensing under Nonuniform Signal and Noise Powers

Abstract

This paper addresses the performance, the reporting channel traffic and the computational complexity of two blind centralized cooperative spectrum sensing schemes under the effect of unequal noise and received signal powers. The first one is the generalized likelihood ratio test with decision fusion, and with weighted and non-weighted data fusion of samples and eigenvalues. The second scheme is the circular folding cooperative power spectral density split cancellation method with data fusion. A total of eight techniques arose from variations of these two in terms of the different fusion and combining rules. It is demonstrated that different configurations of the system parameters may influence the above three metrics in different extents, meaning that none of the techniques is capable of overcoming the others in all metrics simultaneously. This indicates that the choice of the most suitable technique must be carefully made to match the specific scenario to which the technique is intended to be applied. The results presented in this paper serve as guidelines for assisting this choice.