  Intelligent reflecting surfaces (IRSs) 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) has attracted considerable attention recently due to its
advantages in converting multiuser interference (MUI) into useful signal
energy. Therefore, it is of interest to investigate the employment of IRS 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 IRS-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 IRS and illustrate the effectiveness of our proposed
algorithms.
