AI 中文总结
研究节能有源堆叠智能超表面辅助下行链路传输框架，通过联合优化基站波束成形和ASIM配置最大化系统能量效率，利用多种变换和优化方法解决问题，相比传统方法显著提升EE，并研究了相关因素对性能的影响。
AI 中文摘要
本文研究了一种节能有源堆叠智能超表面（ASIM）辅助的下行链路传输框架，其中多天线基站通过多层超表面架构为多个用户服务。与传统无源智能表面不同，所考虑 的ASIM采用有源放大和多个透射层来增强电磁波操纵。我们旨在通过在用户服务质量和放大约束下联合优化基站波束成形和ASIM配置来最大化系统能量效率（EE）。由于级联近场信道和多层超表面结构，由此产生的问题是高度耦合和非凸的。为了应对这一挑战，我们首先通过上图、拉格朗日对偶和二次变换来转换原始问题。然后开发了一种交替优化框架，其中基站波束成形子问题通过逐次凸逼近（SCA）求解，而ASIM配置则使用基于高斯过程替代模型的贝叶斯优化进行优化。数值结果表明，与传统无源SIM和启发式基准方法相比，所提出的方案显著提高了可实现的EE。此外，还研究了放大能力、超表面层数和层间距对系统性能的影响，为未来有源超表面辅助无线网络提供了有用的设计见解。
英文摘要
This paper investigates an energy-efficient active stacked intelligent metasurfaces (ASIM)-assisted downlink transmission framework, where a multi-antenna base station (BS) serves multiple users through a multi-layer metasurface architecture. Unlike conventional passive intelligent surfaces, the considered ASIM employs active amplification and multiple transmissive layers to enhance electromagnetic wave manipulation. We aim to maximize the system energy efficiency (EE) by jointly optimizing the BS beamforming and ASIM configurations under user quality-of-service and amplification constraints. The resulting problem is highly coupled and non-convex due to the cascaded near-field channel and multi-layer metasurface structure. To address this challenge, we first transform the original problem through Dinkelbach, Lagrangian dual, and quadratic transformations. An alternative optimization framework is then developed, where the BS beamforming subproblem is solved via successive convex approximation (SCA), while the ASIM configuration is optimized using Bayesian optimization based on a Gaussian process surrogate model. Numerical results demonstrate that the proposed scheme significantly improves the achievable EE compared to conventional passive SIM and heuristic benchmark methods. Furthermore, the impacts of amplification capability, number of metasurface layers, and inter-layer spacing on system performance are investigated, providing useful design insights for future active metasurface-assisted wireless networks.
CommentsAccepted by IEEE WCL
