Cascaded Channel Statistics and Target Detection Analysis for IRS-Assisted ISAC Employing NOMA

This paper investigates the intelligent reflecting surface (IRS)-assisted integrated sensing and communication (ISAC) framework employing a non-orthogonal multiple access (NOMA) transmission scheme. In the proposed system, an ISAC transceiver employing NOMA transmits information to the down-link near and far users in the presence of the radar target and clutters, with the IRS assisting the far user. The ISAC transceiver communicates with the users while simultaneously performing mono-static sensing to detect the target. For the presented system, a new exact channel statistic for the cascaded Rician-Rayeligh link via IRS is derived using the Laplace transform to address the central limit theorem (CLT) approximation limitation in a low channel gain scenario. Thus, it enables an accurate derivation of the closed-form analytical expression for the outage probability of the system in a high signal-to-noise ratio (SNR) regime, where the optimal phase shifts at the IRS have been employed to improve the received signal at the far user. We have shown that when random phase shifts are employed at the IRS, CLT approximation is satisfied to provide accurate outage probability in all SNR regimes. Our derived analysis thoroughly investigates considering the interference caused by sensing echoes and clutters to the communication users. Further, we have derived the probability of detection of the radar target by employing the Neyman-Pearson criterion and analyzed the receiver operating characteristics for target detection in the presence of clutters. Numerical results demonstrate the proposed analytical framework through Monte-Carlo simulations for various system parameters, and comparative performance analysis reveals that the NOMA-assisted ISAC outperforms orthogonal multiple-access systems.