Energy-Efficient Designs for SIM-Based Broadcast MIMO Systems

Stacked intelligent metasurface (SIM), which consists of multiple layers of intelligent metasurfaces, is emerging as a promising solution for future wireless communication systems. In this timely context, we focus on broadcast multiple-input multiple-output (MIMO) systems and aim to characterize their energy efficiency (EE) performance. To explore the potential of SIM, we consider both dirty paper coding (DPC) and linear precoding (LP) and formulate the corresponding EE maximization problems. For DPC, we employ the broadcast channel (BC)-multiple-access channel (MAC) duality to obtain an equivalent problem, and optimize users' covariance matrices using the successive convex approximation (SCA) and Dinkelbach's methods. Since the phase shift optimization problem of the SIM meta-elements is one of extremely large size, we adopt a conventional projected gradient-based method for its simplicity. A similar approach is followed for the case of LP. Simulation results show that the proposed optimization methods for the considered SIM-based systems can significantly improve the EE, compared to conventional counterparts. Also, we demonstrate that the number of SIM meta-elements and their distribution across the SIM layers have a significant impact on both the achievable sum-rate and EE performance.