Influence of a Direct-Conversion Receiver Model on the Performance of Detectors for Spectrum Sensing

Abstract

An implementation-oriented receiver model for centralized data-fusion cooperative spectrum sensing was proposed a few years ago to assess the performances of the energy detector and some eigenvalue-based detectors. The model is grounded on a direct-conversion receiver whose main influences on the sensing performance have been found to be the direct-current-offset and the automatic gain control. In this paper we improve the referred model and use it to assess the performances of state-of-the-art blind detectors whose computations of the test statistics are among the least complex known to date. These detectors are the Gerschgorin radii and centers ratio (GRCR), the Gini index detector (GID), the Pietra-Ricci index detector (PRIDe), and the locally most powerful invariant test (LMPIT). The energy detector (ED) is also included as a benchmark. It is shown that the performances of all detectors are overestimated if the conventional model (in the sense of signal processing operations not oriented by receiver implementation aspects) is adopted. The ED is the detector whose performance is the most affected by the operations made in the implementation-oriented model. The other detectors are affected in quite similar ways, with an advantage of the PRIDe in most of the situations analyzed.