SIM-Enabled Hybrid Digital-Wave Beamforming for Fronthaul-Constrained Cell-Free Massive MIMO Systems

2025-06-23

AI Summary

To address the high radio-frequency (RF) chain cost and limited fronthaul capacity arising from dense access point (AP) deployment in cell-free massive MIMO (CF-mMIMO) systems, this paper proposes a hybrid architecture integrating reconfigurable intelligent surface (RIS)-enabled analog beamforming with digital signal processing. A novel stacked-RIS structure is introduced to enable dynamic electromagnetic wave manipulation. The design jointly optimizes wave-domain analog beamforming, digital precoding, and fronthaul compression under an alternating optimization framework to tackle the resulting high-dimensional non-convex problem. Simulation results demonstrate that the proposed scheme achieves a weighted sum rate approaching that of fully digital systems, while significantly reducing the number of RF chains. Moreover, it outperforms conventional hybrid architectures across most scenarios, effectively balancing hardware efficiency and spectral efficiency.

Technology Category

• Machine Learning: Hardware-aware ML
• Search and Optimization: Mixed Discrete/Continuous Search
• Cognitive Modeling & Cognitive Systems: Agent Architectures

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health
• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG
• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization

Abstract

As the dense deployment of access points (APs) in cell-free massive multiple-input multiple-output (CF-mMIMO) systems presents significant challenges, per-AP coverage can be expanded using large-scale antenna arrays (LAAs). However, this approach incurs high implementation costs and substantial fronthaul demands due to the need for dedicated RF chains for all antennas. To address these challenges, we propose a hybrid beamforming framework that integrates wave-domain beamforming via stacked intelligent metasurfaces (SIM) with conventional digital processing. By dynamically manipulating electromagnetic waves, SIM-equipped APs enhance beamforming gains while significantly reducing RF chain requirements. We formulate a joint optimization problem for digital and wave-domain beamforming along with fronthaul compression to maximize the weighted sum-rate for both uplink and downlink transmission under finite-capacity fronthaul constraints. Given the high dimensionality and non-convexity of the problem, we develop alternating optimization-based algorithms that iteratively optimize digital and wave-domain variables. Numerical results demonstrate that the proposed hybrid schemes outperform conventional hybrid schemes, that rely on randomly set wave-domain beamformers or restrict digital beamforming to simple power control. Moreover, the proposed scheme employing sufficiently deep SIMs achieves near fully-digital performance with fewer RF chains in most simulated cases, except in the downlink at low signal-to-noise ratios.

Problem

• Reduces RF chains and fronthaul costs in CF-mMIMO systems
• Optimizes hybrid digital-wave beamforming for enhanced performance
• Maximizes weighted sum-rate under fronthaul capacity constraints

Innovation

• Hybrid digital-wave beamforming with SIM
• Dynamic electromagnetic wave manipulation
• Alternating optimization for joint beamforming