Robust Beamforming Design for an IRS-Aided NOMA Communication System With CSI Uncertainty

Abstract

Intelligent reflecting surface (IRS) is a promising technology that provides high throughput in future communication systems and is compatible with various communication techniques, such as non-orthogonal multiple-access (NOMA). This paper studies the downlink transmission of IRS-assisted NOMA communication, considering the practical case of imperfect channel state information (CSI). Aiming to maximize the system sum rate, a robust IRS-aided NOMA design is proposed to jointly find the optimal beamforming vector for the access point and the passive reflection matrix for the IRS. This robust design is realised using the penalty dual decomposition (PDD) scheme, and it is shown that the results have a close performance to their upper bound obtained from the corresponding perfect CSI scenario. The presented method is compatible with both continuous and discrete phase shift elements of the IRS. Our findings show that the proposed algorithms, for both continuous and discrete IRS, have low computational complexity compared to other schemes in the literature. Furthermore, we conduct a performance comparison between the IRS-aided NOMA and the IRS-aided orthogonal multiple access (OMA). This comparison shows that robust beamforming techniques are crucial for the system to reap the advantages of IRS-aided NOMA communication in the presence of CSI uncertainty.