Stacked Intelligent Metasurfaces for Holographic MIMO Aided Cell-Free Networks

TL;DR

This work proposes an uplink SIM-based HMIMO architecture for cell-free networks, integrating stacked intelligent metasurfaces at APs to realize energy-efficient, wave-based beamforming with reduced RF chains. A distributed beamforming framework optimizes SIM coefficients and receiver combiners at each AP, while a central MMSE fusion at the CPU accounts for hardware impairments during final data recovery. A low-complexity layer-by-layer alternating optimization is developed for SIM and RC design, and a detailed complexity and convergence analysis demonstrates polynomial-time scalability and guaranteed convergence. Numerical results show the SIM-based approach outperforms single-layer HMIMO in achievable rate, but hardware impairments at APs and UEs cause rate saturation at high SNR, highlighting practical considerations for deployment and hardware design.

Abstract

Large-scale multiple-input and multiple-output (MIMO) systems are capable of achieving high date rate. However, given the high hardware cost and excessive power consumption of massive MIMO systems, as a remedy, intelligent metasurfaces have been designed for efficient holographic MIMO (HMIMO) systems. In this paper, we propose a HMIMO architecture based on stacked intelligent metasurfaces (SIM) for the uplink of cell-free systems, where the SIM is employed at the access points (APs) for improving the spectral- and energy-efficiency. Specifically, we conceive distributed beamforming for SIM-assisted cell-free networks, where both the SIM coefficients and the local receiver combiner vectors of each AP are optimized based on the local channel state information (CSI) for the local detection of each user equipment (UE) information. Afterward, the central processing unit (CPU) fuses the local detections gleaned from all APs to detect the aggregate multi-user signal. Specifically, to design the SIM coefficients and the combining vectors of the APs, a low-complexity layer-by-layer iterative optimization algorithm is proposed for maximizing the equivalent gain of the channel spanning from the UEs to the APs. At the CPU, the weight vector used for combining the local detections from all APs is designed based on the minimum mean square error (MMSE) criterion, where the hardware impairments (HWIs) are also taken into consideration based on their statistics. The simulation results show that the SIM-based HMIMO outperforms the conventional single-layer HMIMO in terms of the achievable rate. We demonstrate that both the HWI of the radio frequency (RF) chains at the APs and the UEs limit the achievable rate in the high signal-to-noise-ratio (SNR) region.

Figures (9)

• Figure 1: System model of the SIM-aided holographic MIMO in cell-free networks.
• Figure 2: Comparison of the average achievable rate $\overline{R}$ versus the transmit power $\rho$ with different number of APs.
• Figure 3: Comparison of the average achievable rate $\overline{R}$ versus the transmit power $\rho$ with different number of SIM layers.
• Figure 4: Average achievable rate $\overline{R}$ versus the transmit power $\rho$ in the conventional full-digital beamformer and the SIM-based hybrid beamformer.
• Figure 5: Average achievable rate $\overline{R}$ versus the number of AP antennas $M$.