AI 中文总结
针对SIM辅助无小区大规模MIMO系统，提出一种高效交替优化算法，大幅降低混合数字-波波束成形优化的计算复杂度，同时保持和速率性能接近现有算法。
AI 中文摘要
堆叠智能超表面（SIM）作为具备成本效益的波域信号处理能力的架构，近期成为无小区大规模MIMO（CF-mMIMO）等大规模波束成形系统的有潜力方案。然而，现有用于数字与SIM支持的波域波束成形联合优化的算法通常存在过高的计算复杂度。本研究针对采用混合数字-波波束成形的SIM辅助CF-mMIMO系统，提出一种用于加权和速率最大化的高效交替优化（AO）算法。与依赖通用优化求解器或逐元素梯度上升方法的现有方案不同，所提算法基于每个接入点（AP）或每个SIM层更新数字与波域波束成形变量，使每一步都能实现闭式更新。数值结果表明，与现有算法相比，所提算法将计算复杂度降低超过99%，同时实现几乎相同的和速率性能。
英文摘要
Stacked intelligent metasurfaces (SIMs) have recently emerged as a promising architecture for large-scale beamforming systems, including cell-free massive MIMO (CF-mMIMO), due to their cost-effective wave-domain signal processing capabilities. However, existing algorithms for the joint optimization of digital and SIM-enabled wave-domain beamforming typically incur prohibitive computational complexity. In this work, we propose an efficient alternating optimization (AO) algorithm for weighted sum-rate maximization in SIM-assisted CF-mMIMO systems employing hybrid digital-wave beamforming. Unlike prior approaches that rely on general-purpose optimization solvers or per-element gradient ascent methods, the proposed algorithm updates the digital and wave-domain beamforming variables on a per-access point (AP) or per-SIM-layer basis, enabling closed-form updates at each step. Numerical results demonstrate that the proposed algorithm reduces the computational complexity by more than 99\% compared to existing algorithms while achieving nearly identical sum-rate performance.
CommentsIEEE PIMRC 2026
