STAR-RIS-Aided Full-Duplex Communication for Massive MIMO IoT Systems

With the increase in the internet-of-things (IoT) users numbers, the upcoming 6G network is required to deploy smart and efficient connectivity optimization algorithms. These algorithms should guarantee that the cellular network can support more IoT users while maintaining the macro-users' quality of service (QoS). In this paper, we exploit simultaneous transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) in optimizing IoT users' connectivity in full-duplex massive multiple-input-multiple-output (MIMO) networks. Different from Conventional RIS, STAR-RIS can support a full-space smart radio environment, which allows for joint full-duplex self-interference (SI) cancellation in the reflection sub-space and IoT Connectivity optimization in the transmission subspace. Accordingly, we examine a single-cell network with a full-duplex base station (BS). The BS deploys a very large scale, i.e., massive MIMO to serve multiple downlink IoT users with the existing uplink and downlink macro users. The joint SI cancellation and IoT connectivity optimization problem is divided into two subproblems. The first subproblem is to optimize the STAR-RIS reflection, minimizing the SI level. The second is to optimize the IoT connectivity and the RIS transmission coefficients, maximizing the downlink rate. The effectiveness of the proposed STAR-RIS optimization framework is validated by numerical results. It is shown that the STAR-RIS-assisted systems outperform the conventional RIS systems and RIS systems with random phase assignments,