Performance of Inequality Index Detectors Implemented with Direct-Conversion Receivers

Inequality index-based detectors represent promising techniques for cooperative spectrum sensing in cognitive radio networks. While schemes such as the Gini index detector (GID), Pietra-Ricci index detector (PRIDe), Atkinson index detector (AID), and Theil index detector (TID) have been studied, prior work typically assumes ideal conditions with conventional receiver models. The impact of impairments from direct-conversion receivers (DCR), including quantization, clipping, and DC-offset, remains underexplored. This work addresses that gap by evaluating these detectors under both conventional and DCR-based models. Results show that PRIDe is the most robust, while TID is particularly sensitive to realistic distortions.