Robust Cooperative Spectrum Sensing for MIMO Cognitive Radio Networks under CSI Uncertainty

This paper considers the problem of cooperative spectrum sensing in multiuser multiple-input multiple-output cognitive radio networks considering the presence of uncertainty in the channel state information (CSI) of the secondary user channels available at the fusion center. Several schemes are proposed that employ cooperative decision rules based on local sensor decisions transmitted to the fusion center by the cooperating nodes over an orthogonal multiple access channel. First, fusion rules are derived under perfect CSI at the fusion center for both antipodal and nonantipodal signaling. Then, a robust detector, termed the uncertainty statistics-based likelihood ratio test, which optimally combines the decisions of different secondary users, is obtained for scenarios with CSI uncertainty. A generalized likelihood ratio test based robust detector is also derived for this scenario. Closed-form expressions are obtained to characterize the probabilities of false alarm $(P-{\text{FA}})$ and detection $(P-D)$ at the fusion center. Simulation results are presented to compare the performance of the proposed schemes with that of the conventional uncertainty agnostic detectors and also to corroborate the analytical expressions developed.