Multiuser NOMA With Multiple Reconfigurable Intelligent Surfaces for Backscatter Communication in a Symbiotic Cognitive Radio Network

In this paper, we develop an optimization framework for the symbiotic operation of a multiuser cognitive radio network (CRN) consisting of a non-orthogonal multiple access (NOMA)-based primary network (PN) and a reconfigurable intelligent surface (RIS)-based secondary network (SN) sharing the same spectrum. In the symbiotic relationship formed in this system model, the RIS devices' PN signal backscattering not only provides multiple primary receivers with a spatial diversity gain but also supports the transmission of the RIS devices' own data to their designated receiver. First, through investigation of a simple network configuration, we obtain insights into the impacts of various factors on the system performance, and thus, into the importance of radio resource allocation for CRN symbiotic operation. Then, we develop a resource allocation framework that maximizes the sum rate of the PN and SN by jointly optimizing the system resources for cases of devices with hardware imperfections. To reduce the complexity of solving this problem, we convert it into a convex weighted minimum mean square error problem. An iterative algorithm for finding the optimal NOMA power allocation for the PN and the reflection coefficients of the RISs is developed, and its overhead is analyzed. Simulation results demonstrate that the proposed algorithm outperforms various benchmarks.