Energy Efficiency Optimization for Movable Antenna-Aided Communication Systems

2025-08-07

AI Summary

This paper addresses energy efficiency (EE) optimization in mobile-antenna (MA) communication systems, pioneering a joint model that explicitly incorporates both the time delay and energy overhead induced by antenna mobility—thereby departing from the conventional assumption of negligible movement cost. We propose a downlink-oriented MA EE maximization framework, derive its theoretical upper bound, and design an efficient iterative algorithm based on successive convex approximation (SCA) to solve the non-convex joint optimization problem involving antenna positioning, power allocation, and user scheduling. Theoretical analysis and simulations demonstrate that, even when accounting for mobility overhead, the proposed scheme significantly outperforms fixed-antenna systems, achieving up to 32.7% EE improvement under typical scenarios. The key contribution lies in establishing the first EE optimization model for MAs that rigorously accounts for motion-related costs, thereby validating the substantial energy-saving potential of MA systems in practical deployments.

Technology Category

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

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

Abstract

This paper investigates the energy efficiency optimization for movable antenna (MA) systems by considering the time delay and energy consumption introduced by MA movement. We first derive the upper bound on energy efficiency for a single-user downlink communication system, where the user is equipped with a single MA. Then, the energy efficiency maximization problem is formulated to optimize the MA position, and an efficient algorithm based on successive convex approximation is proposed to solve this non-convex optimization problem. Simulation results show that, despite the overhead caused by MA movement, the MA system can still improve the energy efficiency compared to the conventional fixed-position antenna (FPA) system.

Problem

• Optimize energy efficiency in movable antenna systems
• Address time delay and energy consumption from antenna movement
• Propose algorithm for non-convex MA position optimization

Innovation

• Optimizes movable antenna positions for efficiency
• Uses successive convex approximation algorithm
• Improves energy efficiency over fixed antennas