Statistical Multiport-Network Modeling and Efficient Discrete Optimization of RIS

2025/08/03 by Cheima Hammami, Hammami, Cheima, Luc Le Magoarou +3 · 1 citation
Engineering · Physics and Astronomy · #Advanced Wireless Communication Technologies #Advanced Antenna and Metasurface Technologies #Electromagnetic Scattering and Analysis

paper · pdf · doi:10.48550/arxiv.2508.01776

Abstract

This Letter addresses the physics-consistent optimization of reconfigurable intelligent surfaces (RISs) with mutual coupling (MC) and 1-bit-programmable RIS elements. This combination of constraints is typical of current prototypes but unexplored in theoretical work. First, we present a simple statistical generator for multiport-network-theory (MNT) parameters of rich-scattering, RIS-parametrized channels. We account for reciprocity, passivity, and coherent backscattering; then, we add a simple hyper-parameter to control the MC strength. Second, we benchmark model-agnostic (dictionary search, coordinate descent, genetic algorithm) and model-based (temperature-annealed back-propagation) strategies under varying MC, with and without intelligent initialization. Except when MC is negligible, coordinate descent with random initialization offers the best trade-off in performance, runtime, and memory. Our insights can guide wireless practitioners who optimize RIS prototypes and other reconfigurable wave systems.

Citations

• Ambiguity-Aware Segmented Estimation of Mutual Coupling in Large RIS: Algorithm and Experimental Validation
• Experimental Multiport-Network Parameter Estimation and Optimization for Multi-Bit RIS
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Cited by

• Frozen differential scattering in reconfigurable complex media
• Ambiguity-Aware Segmented Estimation of Mutual Coupling in Large RIS: Algorithm and Experimental Validation

Related

• Beyond-Diagonal RIS Architecture Design and Optimization under Physics-Consistent Models
• Reconfigurable Intelligent Surfaces and Capacity Optimization: A Large System Analysis
• Multi-RIS-Empowered Communication Systems: Capacity Analysis and Optimization
• Capacity Optimization using Reconfigurable Intelligent Surfaces: A Large\n System Approach
• Experimental Multiport-Network Parameter Estimation and Optimization for Multi-Bit RIS