Joint Symbol-Level Precoding and Reflecting Designs for RIS-Enhanced MU-MISO Systems

Reconfigurable intelligent surfaces (RIS) have emerged as a revolutionary solution to enhance wireless communications by changing propagation environment in a cost-effective and hardware-efficient fashion. In addition, symbol-level precoding (SLP) technique has attracted considerable attention recently due to its advantages in converting multiuser interference (MUI) into useful signals. Therefore, it is of interest to investigate the employment of RIS in symbol-level precoding systems to exploit MUI in a more effective way by manipulating the multiuser channels. In this paper, we focus on joint symbol-level precoding and reflecting designs in RIS-enhanced multiuser multiple-input single-output (MU-MISO) systems. Both power minimization and quality-of-service (QoS) balancing problems are considered. In order to solve the joint optimization problems, we develop an efficient iterative algorithm to decompose them into separate symbol-level precoding and block-level reflecting design problems. An efficient gradient-projection-based algorithm is utilized to design the symbol-level precoding and a Riemannian conjugate gradient (RCG)-based algorithm is employed to solve the reflecting design problem. Simulation results demonstrate the significant performance improvement introduced by the RIS and illustrate the effectiveness of our proposed algorithms.