Physics-Compliant Modeling and Optimization of MIMO Systems Aided by Microwave Linear Analog Computers

2026-02-22

AI Summary

This study addresses the neglect of antenna mutual coupling in existing metasurface-inspired large intelligent reflecting surface (MiLAC)-assisted MIMO research, which leads to model inaccuracies. Building upon multiport network theory, this work develops a physically consistent end-to-end MiLAC-MIMO model and proposes a mutual coupling-aware optimization framework to maximize received power. It is the first to reveal that mutual coupling inherently provides an averaging gain in MiLAC systems, demonstrating that such systems achieve performance equivalent to digital architectures equipped with impedance matching networks—yet require fewer RF chains—and consistently outperform configurations without matching networks. By leveraging convex optimization and closed-form solutions, the paper derives three analytical performance bounds, which are validated through extensive simulations.

Technology Category

• Machine Learning: Optimization
• Search and Optimization: Metareasoning and Metaheuristics
• Multiagent Systems: Mechanism Design

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Security and Privacy: Large-scale security measurements

Abstract

Microwave linear analog computer (MiLAC) has emerged as a promising architecture for implementing linear multiple-input multiple-output (MIMO) processing in the analog domain, with radio frequency (RF) signals. Existing studies on MiLAC-aided communications rely on idealized channel models and neglect antenna mutual coupling. However, since MiLAC performs processing at RF, mutual coupling becomes critical and alters the implemented operation, not only the channel characteristics. In this paper, we develop a physics-compliant model for MiLAC-aided MIMO systems accounting for mutual coupling with multiport network theory. We derive end-to-end system models for scenarios with MiLACs at the transmitter, the receiver, or both, showing how mutual coupling impacts the linear transformation implemented by the MiLACs. Furthermore, we formulate and solve a mutual coupling aware MiLAC optimization problem, deriving a closed-form globally optimal solution that maximizes the received signal power. We establish the fundamental performance limits of MiLAC with mutual coupling, and derive three analytical results. First, mutual coupling is beneficial in MiLAC-aided systems, on average. Second, with mutual coupling, MiLAC performs as digital architectures equipped with a matching network, while having fewer RF chains. Third, with mutual coupling, MiLAC always outperforms digital architectures with no matching network. Numerical simulations confirm our theoretical findings.

Problem

• mutual coupling
• MIMO systems
• microwave linear analog computer
• RF signal processing
• physical modeling

Innovation

• microwave linear analog computer
• mutual coupling
• MIMO systems
• multiport network theory
• physics-compliant modeling