Energy-Efficient Movable Antennas: Mechanical Power Modeling and Performance Optimization

2025-09-29

AI Summary

This paper addresses energy efficiency (EE) optimization in movable-antenna (MA) systems by jointly optimizing antenna positioning, mobility velocity, and multi-user precoding at the base station, while explicitly modeling mechanical power consumption induced by stepper motors. To eliminate collision constraints, a novel antenna renumbering strategy is proposed. The implicit monotonicity of EE with respect to mobility velocity is analytically revealed. An integrated bi-level optimization framework is developed: the outer layer handles the fractional EE programming via the Dinkelbach method, while the inner layer employs alternating optimization (AO) to iteratively update antenna positions, velocities, and beamforming vectors. Numerical results demonstrate that the proposed algorithm significantly enhances system EE in multi-user scenarios, outperforming conventional fixed-antenna systems and state-of-the-art energy-efficiency benchmarks.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• 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 antennas (MAs) offer additional spatial degrees of freedom (DoFs) to enhance communication performance through local antenna movement. However, to achieve accurate and fast antenna movement, MA drivers entail non-negligible mechanical power consumption, rendering energy efficiency (EE) optimization more critical compared to conventional fixed-position antenna (FPA) systems. To address this issue, we develop a fundamental power consumption model for stepper motor-driven multi-MA systems based on electric motor theory. Based on this model, we formulate an EE maximization problem from a multi-MA base station (BS) to multiple single-FPA users. We aim to jointly optimize the MAs' positions, moving speeds, and the BS's transmit precoding matrix subject to collision-avoidance constraints during the multi-MA movements. However, this problem is difficult to solve. To tackle this challenge, we first reveal that the collision-avoidance constraints can always be relaxed without loss of optimality by properly renumbering the MA indices. For the resulting relaxed problem, we first consider a simplified single-user setup and uncover a hidden monotonicity of the EE performance with respect to the MAs' moving speeds. To solve the remaining optimization problem, we develop a two-layer optimization framework. In the inner layer, the Dinkelbach algorithm is employed to derive the optimal beamforming solution for any given MA positions. In the outer layer, a sequential update algorithm is proposed to iteratively refine the MA positions based on the optimal values obtained from the inner layer. Next, we proceed to the general multi-user case and propose an alternating optimization (AO) algorithm. Numerical results demonstrate that despite the additional mechanical power consumption, the proposed algorithms can outperform both conventional FPA systems and other existing EE maximization benchmarks

Problem

• Modeling mechanical power consumption in movable antenna systems
• Optimizing energy efficiency for multi-antenna base stations
• Solving joint optimization of antenna positions and beamforming

Innovation

• Modeled mechanical power for movable antenna systems
• Developed two-layer optimization for beamforming and positions
• Proposed alternating optimization algorithm for multi-user case