PhysFad: Physics-Based End-to-End Channel Modeling of RIS-Parametrized Environments with Adjustable Fading

Abstract

Programmable radio environments parametrized by reconfigurable intelligent surfaces (RISs) are emerging as a new wireless communications paradigm, but currently used channel models for the design and analysis of signal-processing algorithms cannot include fading in a manner that is faithful to the underlying wave physics. To overcome this roadblock, we introduce a physics-based end-to-end model of RIS-parametrized wireless channels with adjustable fading (coined PhysFad) which is based on a first-principles coupled-dipole formalism. PhysFad naturally incorporates the notions of space and causality, dispersion (i.e., frequency selectivity) and the intertwinement of each RIS element's phase and amplitude response, as well as any arising mutual coupling effects including long-range mesoscopic correlations. PhysFad offers the to-date missing tuning knob for adjustable fading. We thoroughly characterize PhysFad and demonstrate its capabilities for a prototypical problem of RIS-enabled over-the-air channel equalization in rich-scattering wireless communications. We also share a user-friendly version of our code to help the community transition towards physics-based models with adjustable fading.

30 pages, 7 figures, submitted to an IEEE Journal

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• On the Impact of Control Signaling in RIS-Empowered Wireless Communications
• XR-RF Imaging Enabled by Software-Defined Metasurfaces and Machine Learning: Foundational Vision, Technologies and Challenges
• Self-Adaptive RISs Beyond Free Space: Convergence of Localization, Sensing and Communication under Rich-Scattering Conditions
• Control of the Scattering Properties of Complex Systems By Means of Tunable Metasurfaces
• A self-adaptive RIS that estimates and shapes fading rich-scattering wireless channels
• Simultaneous Active and Passive Information Transfer for RIS-Aided MIMO Systems: Iterative Decoding and Evolution Analysis
• Time Domain Generalization of the Random Coupling Model and Experimental Verification in a Complex Scattering System
• Realistic Evaluation of Impedance-Based RIS Modeling: Practical Insights and Applications
• Reconfigurable Intelligent Surfaces in Dynamic Rich Scattering Environments: BiLSTM-Based Optimization for Accurate User Localization
• AI-Aided Annealed Langevin Dynamics for Rapid Optimization of Programmable Channels