ED based spectrum sensing over IRS-assisted Rayleigh-FTR fading channels

Abstract

A recent study has revealed that incorporating intelligent reflecting surfaces (IRS) into wireless systems improves their performance within various signal propagation conditions. This research paper focuses on evaluating the spectrum-sensing abilities of cognitive radio in wireless environments enhanced by IRS technology. To achieve this, the paper develops a statistical model to describe the connections between the primary user (PU) and IRS, as well as between IRS and the secondary user (SU). This model calculates a precise approximation of the probability density function (PDF) of the end-to-end instantaneous signal-to-noise ratio (SNR). The SNR considers both the PU-to-IRS link, which follows a Rayleigh fading distribution, and the IRS-to-SU link, which follows an FTR fading distribution. By utilizing this PDF distribution, the paper derives analytical expressions for the average probability of detection (APD) for single and cooperative secondary users. These APD expressions are then employed to establish the exact closed-form expression for the average area under the receiver operating characteristics (AUC), system throughput, and transmission probability of the SU. To validate these theoretical findings, the paper conducts Monte Carlo simulations. The results from these simulations indicate an improved detection probability when operating in an IRS-enhanced wireless propagation environment. Consequently, the study suggests that incorporating IRS technology can significantly enhance the reliability of communication systems based on cognitive radio principles.