可重构无线系统的物理一致性信道建模与信号处理
Physically Consistent Channel Modeling and Signal Processing for Reconfigurable Wireless Systems
AI总结：
本教程针对可重构无线系统，开发涵盖可重构天线架构、物理一致性信道建模与信号处理的统一框架，为端到端设计提供基础，解决传统信道模型的相关假设挑战。
AI中文摘要：
可重构天线正越来越多地集成到多天线通信系统中，以利用大孔径，同时降低传统大规模阵列的硬件复杂度、能耗和实现成本。其可重构电磁（EM）特性，包括动态变化的辐射方向图和依赖状态的互耦，对传统信道模型的固定天线和解耦端口假设提出了挑战。这推动了一种连接麦克斯韦方程、电路理论和信息论的物理一致性框架的发展。在本教程中，我们开发了一个涵盖三个耦合维度的统一框架：（i）可重构天线和收发信机架构，（ii）物理一致性信道建模，（iii）物理一致性信号处理。我们首先建立了涵盖可调天线、可重构收发信机和新兴阵列架构的分类，强调其重构机制和硬件-性能权衡。然后，我们开发了基于麦克斯韦方程、波数域表示、多端口网络理论和计算电磁学的建模方法，并使用这些方法构建端到端信道和噪声模型，以捕捉近场传播、互耦和电路级损伤。在这些模型的基础上，我们研究了架构感知的信道估计、波束成形、数据检测和信道解码，强调物理结构如何重塑算法设计和性能-复杂度权衡。总体而言，本教程将物理架构、信道和噪声模型以及通信算法视为端到端设计的耦合组件，为物理一致性可重构无线系统提供了统一基础。
英文摘要：
Reconfigurable antennas are increasingly integrated into multi-antenna communication systems to exploit large apertures while reducing the hardware complexity, energy consumption, and implementation costs of classical massive arrays. Their reconfigurable electromagnetic (EM) properties, including dynamically varying radiation patterns and state-dependent mutual coupling, challenge the fixed-antenna and decoupled-port assumptions of conventional channel models. This motivates a physically consistent framework connecting Maxwell's equations, circuit theory, and information theory. In this tutorial, we develop a unified framework spanning three coupled dimensions: (i) reconfigurable antenna and transceiver architectures, (ii) physically consistent channel modeling, and (iii) physically consistent signal processing. We first establish a taxonomy covering tunable antennas, reconfigurable transceivers, and emerging array architectures, highlighting their reconfiguration mechanisms and hardware-performance trade-offs. We then develop modeling approaches based on Maxwell's equations, wavenumber-domain representations, multiport network theory, and computational electromagnetics, and use them to construct end-to-end channel and noise models that capture near-field propagation, mutual coupling, and circuit-level impairments. Building on these models, we examine architecture-aware channel estimation, beamforming, data detection, and channel decoding, emphasizing how physical structure reshapes algorithm design and performance-complexity trade-offs. Overall, the tutorial treats physical architecture, channel and noise models, and communication algorithms as coupled components of an end-to-end design, providing a unified foundation for physically consistent reconfigurable wireless systems.
