Suppressing the Effects of Aliasing and IQ Imbalance on Multiband Spectrum Sensing

In cognitive radio networks, secondary users (SUs) can use a frequency band when the primary user (PU) of the band is not transmitting. Spectrum sensing is one of the methods that SUs employ to know if the PU has stopped transmitting. Accurate spectrum sensing boosts the likelihood that an SU detects a spectrum opportunity. However, it will be challenging for affordable receivers to support accurate spectrum sensing due to receiver impairments, including IQ imbalance and aliasing. Several other papers have developed methods that can address the effects of IQ imbalance in spectrum sensing. This paper presents a technique that can address not only IQ imbalance but the effects of aliasing on multiband spectrum sensing as well. We use channelized spectrum-domain modeling of receivers to develop the technique. This paper presents the theoretical development of the receiver modeling technique and the proposed spectrum sensing mechanism. The performance of the proposed mechanism is evaluated using simulations and hardware-based measurements. The results demonstrate that the proposed mechanism significantly enhances the opportunity detection probability of affordable cognitive radios with high IQ imbalance and poor antialiasing filter selectivity performances.