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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 gain a comprehensive understanding of the potential of SIM, we consider both dirty paper coding (DPC) and linear precoding 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) method, which is based on a tight lower bound of the achievable sum-rate, in combination with Dinkelbach's method. Since optimizing the phase shifts of the SIM meta-elements is an optimization problem of extremely large size, we adopt a conventional projected gradient-based method for its simplicity. A similar approach is derived for the case of linear precoding. Simulation results show that the proposed optimization methods for the considered SIM-based systems can significantly improve the EE, compared to the 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., Comment: 13 pages, 6 figures

In this paper, we propose a new hybrid analog and digital combining architecture for millimeter wave (mmWave) multi-user multiple-input multiple-output (MU-MIMO) systems. The proposed structure employs antenna subset selection per radio frequency (RF) chain based on active/inactive switches and uses constant phase shifters (CPS) to control the phases of signals in the RF circuit. In this scheme, for each RF chain, a subset of receive antennas that contribute more to the desired signal power than the interference power is chosen for signal combining in the analog domain, whereas other receive antennas are excluded from signal combining, thereby enhancing sum-rates. Simultaneously, the proposed structure reduces power consumption in the RF circuit by exclusively activating switches that correspond to the antennas selected for each RF chain. We also develop three low-complexity algorithms for per-RF chain antenna subset selection. Finally, through numerical simulation, we show that the proposed structure provides higher spectral efficiency and higher energy efficiency than conventional hybrid analog and digital combining schemes for mmWave MU-MIMO systems., Comment: 28 pages, 11 figures