Sum Rate Maximization in STAR-RIS-Assisted Uplink AmBC-CR Networks with NOMA

In this paper, we investigate a network of backscatter devices (BDs) empowered with cognitive radio (CR) that uses non-orthogonal multiple access (NOMA) to communicate with the backscatter receiver. The presence of dual fading in backscatter networks weakens the strength of the backscatter link, thus impacting achievable performance. To address this issue, reconfigurable intelligent surfaces (RIS) can be used in such networks. However, the conventional RIS provides half-space coverage. Therefore, the use of simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) can offer services to BDs in a full-space. Consequently, we jointly optimize the reflection/transmission (R/T) phase shift matrices, the R/T periods at the STAR-RIS, and the power reflection coefficients (PRCs) at the BDs to maximize the sum rate in the STAR-RIS-assisted NOMA-enabled AmBC-CR (SRIS-NeAmCR) networks, subject to the quality of service (QoS) constraints of individual BDs and the primary receiver. We introduce an approach to solve the resulting non-convex optimization problem by employing semidefinite relaxation and rank-one approximation, seeking a suboptimal solution through an alternating optimization algorithm. The simulation results show that the proposed scheme works better than the baseline schemes like NOMA without STAR-RIS, NOMA with random phases, orthogonal multiple access (OMA) without STAR-RIS, and OMA with optimal phases.