基于阻塞检测与闭式黎曼更新的端到端感知移动性的多可重构智能表面优化
End-to-End Mobility-Aware Multi-RIS Optimization via Blockage Detection and Closed-Form Riemannian Updates
AI总结：
该研究针对毫米波多用户MIMO系统的RIS链路阻塞问题，提出集成阻塞检测与SCRPA算法的多RIS优化框架，仿真验证其可提升加权和速率与可扩展性。
AI中文摘要：
毫米波（mmWave）多用户MIMO系统极易受动态阻塞影响，可重构智能表面（RIS）被作为解决方案引入，但RIS链路自身也可能被阻塞，而现有研究常假设其理想可用。本文提出一种端到端感知移动性的多RIS优化框架，将每个RIS的阻塞检测与闭式黎曼更新相结合：基站发送短的索引同步信号，使各用户通过简单能量测试识别被阻塞的面板；基于检测到的可行集，采用随机闭式黎曼相位对齐（SCRPA）算法联合优化基站预编码器与RIS相位，该算法保证模约束可行性、单调收敛性与低复杂度；大量仿真验证了可靠的阻塞检测，并表明与现有基线相比，加权和速率与可扩展性均有显著提升。
英文摘要：
Millimeter-wave (mmWave) multi-user MIMO systems are highly susceptible to dynamic blockages, and reconfigurable intelligent surfaces (RIS) have been introduced as a remedy. However, RIS links can themselves be blocked, while existing studies often assume ideal availability. This paper proposes an end-to-end mobility-aware multi-RIS optimization framework that integrates per-RIS blockage detection with closed-form Riemannian updates. The base station transmits short indexed synchronization signals, enabling each user to identify blocked panels via a simple energy test. Based on the detected feasible sets, we jointly optimize the BS precoder and RIS phases using a Stochastic Closed-form Riemannian Phase Alignment (SCRPA) algorithm, which ensures unit-modulus feasibility, monotone convergence, and low complexity. Extensive simulations validate reliable blockage detection and demonstrate significant weighted sum-rate and scalability gains compared to existing baselines.
