Robust and Blind Eigenvalue-Based Multiantenna Spectrum Sensing Under IQ Imbalance

We investigate the spectrum sensing problem in a single-input-multiple-output cognitive radio system under in-phase and quadrature imbalance (IQI). To do this, the received signal model is obtained in the presence of IQI at the analog front-ends of both the primary and secondary users. We first use a preprocessing stage to mitigate the effect of receiver IQI (RX-IQI). It is found that the received matrix signal is composed of an unknown rank-2 matrix contaminated by the receiver noise matrix. Then, we apply the likelihood ratio test principle to develop three eigenvalue-based detectors. Analytical expressions for the false alarm probabilities of the proposed detectors are derived to adjust their detection thresholds, especially under noise variance uncertainty. Simulation results are provided to illustrate the spectrum sensing performance of the proposed detectors in comparison with existing detectors in the literature also to verify the analytical expressions derived for the false alarm probability. Our simulation results show that the proposed spectrum sensing algorithms are not susceptible to the RX-IQI effects. In addition, we analytically show that one of the proposed spectrum sensing algorithms has constant false alarm rate property with respect to the noise variance uncertainty.