AI 中文总结
本文提出模块化框架TRACE及DCAR算法，通过分离各模块实现RIS相关研究的可复现评估，DCAR可降低导频与计算开销并保持波束成形性能。
AI 中文摘要
可重构智能表面（Reconfigurable Intelligent Surface，RIS）研究将信道估计、控制与通信紧密结合，但现有实现通常依赖固定算法流程，难以在相同条件下对比不同的估计、跟踪及通信策略，也难以研究时变信道下低开销的RIS自适应。本文通过两项互补贡献解决这两个挑战：其一，提出TRACE（用于RIS辅助信道估计、自适应控制与通信实验的工具包），这是一个基于套接字的模块化框架，通过独立的控制平面与数据平面接口分离发射机、无线电环境、控制器和接收机，支持可替换模块的可复现评估；其二，提出差分信道感知RIS更新（Differential Channel-Aware RIS Update，DCAR）算法，该算法利用正则化差分更新从减少的导频观测中估计信道扰动，以降低重训练开销。TRACE通过可替换的最小均方误差、正交匹配追踪信道估计，高斯随机游走、高斯-马尔可夫信道演化，BPSK、QPSK和16-QAM调制技术，以及多种RIS尺寸进行验证，无需修改底层框架。在TRACE中，DCAR被观察到可降低导频开销和计算复杂度，同时在时变信道下保持接近基于卡尔曼滤波跟踪的波束成形性能。
英文摘要
Reconfigurable Intelligent Surface (RIS) research tightly couples channel-estimation, control and communication, yet existing implementations often rely on fixed algorithmic pipelines, making it difficult to compare alternative estimation, tracking and communication strategies under identical conditions and to study low-overhead RIS adaptation under time-varying channels. This paper addresses both challenges through two complementary contributions. First, it presents TRACE (Toolkit for RIS-assisted channel-estimation, adaptive control and communication experimentation), a modular socket-based framework that decouples the transmitter, radio environment, controller and receiver through separate control- and data-plane interfaces, enabling reproducible evaluation across substitutable modules. Second, it proposes the differential channel-aware RIS update (DCAR) algorithm, which estimates channel perturbations from reduced probe observations using a regularized differential update to reduce retraining overhead. TRACE is validated through interchangeable minimum mean square error and orthogonal matching pursuit channel-estimation, Gaussian random walk and Gauss--Markov channel evolution, BPSK, QPSK and 16-QAM modulation techniques and multiple RIS sizes, without modifying the underlying framework. Within TRACE, DCAR is observed to reduce pilot overhead and computational complexity while maintaining beamforming performance close to Kalman-filter-based tracking under time-varying channels.
Comments14 pages, 18 figures, Submitted to IEEE TCoM for review on 18th July 2026
