Rethinking Mutual Coupling in Movable Antenna MIMO Systems

2026-03-13

AI Summary

This study addresses the long-overlooked impact of mutual coupling induced by antenna movement in mobile MIMO systems, which has constrained capacity gains. For the first time, mutual coupling is systematically incorporated into a circuit-theoretic model for point-to-point MIMO communication, and the capacity maximization problem is formulated as a non-concave optimization. To solve this, the authors propose a block coordinate ascent algorithm combined with a trust-region method. A key innovation lies in efficiently computing the derivative of the inverse square root of the mutual coupling matrix via the Sylvester equation, enabling joint optimization of antenna positions and the coupling matrix. Simulations demonstrate that tailoring the mutual coupling structure and exploiting superdirectivity significantly enhance system capacity.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Non-convex Optimization
• Machine Learning: Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Movable antenna (MA) systems have emerged as a promising technology for future wireless communication systems. The movement of antennas gives rise to mutual coupling (MC) effects, which have been previously ignored and can be exploited to enhance the capacity of multiple-input multiple-output (MIMO) systems. To this end, we first model an MA-enabled point-to-point MIMO communication system with MC effects using a circuit-theoretic framework. The capacity maximization problem is then formulated as a non-concave optimization problem and solved via a block coordinate ascent (BCA)-based algorithm. The subproblem of optimizing MA positions is challenging due to the presence of the analytically intractable MC matrices. To overcome this difficulty, we develop a trust region method (TRM)-based algorithm to optimize MA positions, wherein Sylvester equations are employed to compute the derivatives of the inverse square roots of the MC matrices. Simulation results show significant capacity gains from leveraging MC effects, primarily due to customizable MC matrices and superdirectivity.

Problem

• movable antenna
• mutual coupling
• MIMO systems
• capacity maximization
• antenna positioning

Innovation

• movable antenna
• mutual coupling
• MIMO capacity
• trust region method
• superdirectivity