GLRT-Based Spectrum Sensing for SIMO Cognitive Radio with Transmitter IQI

摘要

In this work, the received signal of a single-input-multiple-output (SIMO) cognitive radio (CR) is modeled under transmission in-phase and quadrature imbalance (TX-IQI). Then, the detection problem is presented as a composite hypothesis testing problem. Based on the generalized likelihood ratio test (GLRT) principle, two eigenvalue-based detectors are derived in the case of known and unknown noise variance. This results in different detectors. The first is a non-constant false alarm rate (CFAR) test with respect to the noise variance, referred to as semi-blind GLR (SBG) test. The latter is a CFAR detector called blind GLR (BG). For the proposed non-CFAR detector, we introduce a new threshold setting to restrict its obtained false alarm to an upper bound$p_{fa}$, improving the chance of opportunistic use of spectrum holes. Detection performance of proposed detectors is compared in different scenarios through extensive Monte-Carlo simulations. It is shown that the BG test outperforms the SBG detector in the presence of noise variance uncertainty as well as TX-IOI.