Rate-splitting for intelligent reflecting surface-assisted CR-NOMA systems

Abstract

Intelligent reflecting surface (IRS) has been regarded as promising technique to improve system performance for wireless communications. In this paper, we propose a rate-splitting (RS) scheme for an IRS-assisted cognitive radio-inspired non-orthogonal multiple access (CR-NOMA) system, where the primary user's (PU's) quality of service (QoS) requirements must be guaranteed to be same as in orthogonal multiple access. Assisted by IRS, the threshold for the PU's tolerable interference power is improved, which in turn makes it possible to increase the achievable rate for the secondary user (SU). The optimal transmit power allocation, target rate allocation, and successive interference cancellation (SIC) decoding order are jointly designed for the proposed RS scheme. Taking into account the statistics of the direct link and IRS reflecting channels, closed-form expression for the PU's and SU's outage probabilities are respectively derived. Various simulation results are presented to clarify the enhanced outage performance achieved by the proposed RS scheme over the existing CR-NOMA and IRS-assisted CR-NOMA schemes.