Precoding-free Hierarchical Rate-Splitting Multiple Access via Stacked Intelligent Metasurface

2025-10-28

AI Summary

To address hardware complexity and baseband overhead bottlenecks arising from interference management in dense multi-antenna networks, this paper proposes a digital-precoding-free hierarchical Rate-Splitting Multiple Access (RSM-NOMA) architecture. The method leverages stacked Intelligent Ultra-Surfaces (IUS) to achieve user separation and interference suppression in the wave domain, integrated with scalar power allocation, clustering-based user grouping, and SPSA-driven joint phase–power optimization to efficiently solve the underlying non-convex problem. Simulation results demonstrate that, under significantly reduced active antenna counts, the proposed scheme achieves higher minimum user rate than benchmark approaches—including hybrid beamforming—while substantially improving spectral efficiency, user fairness, and energy efficiency. Moreover, it offers superior scalability and hardware simplification.

Technology Category

• Machine Learning: Hardware-aware ML
• Intelligent Robots: Multi-Robot Systems
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

Interference management is a central bottleneck in dense multi-antenna wireless networks. Therefore, in this study, we present a digital precoding-free hierarchical rate-splitting multiple access (HRSMA) architecture assisted by a stacked intelligent metasurface (SIM) to achieve high spectral efficiency and user fairness with reduced hardware complexity. In the proposed system, the base station performs only scalar power allocation, while a multi-layer SIM acts as a wave-domain processor that spatially separates users and mitigates interference via nonlinear wavefront reconfiguration. This design eliminates the need for digital or hybrid precoding, drastically reducing the baseband computations. A joint optimization problem is formulated to maximize the minimum user rate by jointly optimizing SIM phase shifts, power allocation, and user grouping. To efficiently solve the resulting non-convex problem, an alternating optimization algorithm is developed, combining simultaneous perturbation stochastic approximation (SPSA) for SIM configuration and power control with clustering-based grouping refinement. Simulation results demonstrate that the proposed SIM-aided HRSMA achieves substantial gains in both spectral efficiency and fairness compared to hybrid beamforming and non-precoding baselines. Specifically, SIM-aided HRSMA attains comparable or superior minimum rates with significantly fewer active antennas by exploiting the additional wave-domain degrees of freedom provided by multi-layer SIMs. These findings highlight the potential of SIM-aided HRSMA as a low-cost, energy-efficient, and scalable solution for beyond-6G networks.

Problem

• Eliminating digital precoding in dense wireless networks
• Managing interference via stacked intelligent metasurface technology
• Optimizing spectral efficiency and user fairness simultaneously

Innovation

• Precoding-free hierarchical rate-splitting via stacked metasurface
• Multi-layer metasurface spatially separates users and mitigates interference
• Joint optimization of phase shifts, power allocation, and grouping