Trajectory Design for Fairness Enhancement in Movable Antennas-Aided Communications

2026-04-22

AI Summary

This work addresses the challenge of achieving rate fairness among multiple users in uplink communications, where the geometric configuration of antenna arrays typically entails inherent trade-offs. To overcome this limitation, the paper proposes optimizing the trajectory of movable base station antennas to maximize the minimum achievable rate across all users within a finite time horizon. Theoretical analysis demonstrates that the optimal antenna placement can be selected from a finite set of configurations. Building on this insight, the authors first solve the continuous-time optimization problem under an idealized unlimited-velocity assumption using Lagrangian duality, and then develop a heuristic trajectory algorithm tailored to practical velocity constraints. Numerical results show that the proposed approach significantly outperforms existing benchmarks and offers marked advantages in ensuring communication fairness among users.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search
• Machine Learning: Optimization

Application Category

• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Through adaptive antenna repositioning, the movable antenna (MA) technology enables on-demand reconfiguration of wireless channels, thereby creating an additional spatial degree of freedom in improving communication performance. This paper investigates a multiuser uplink communication system aided by MAs, where a base station (BS) equipped with multiple MAs serves multiple single-antenna users. Specifically, given that an optimized array geometry cannot guarantee rate fairness, we focus on designing antenna trajectory at the BS to maximize the minimum achievable rate among all users over a finite time period. The resulting optimization problem is fundamentally challenging to solve due to the continuous-time nature. To address it, we first examine an ideal case with infinitely fast MA movement and demonstrate that the relaxed problem can be optimally solved via the Lagrangian dual method. The obtained trajectory solution reveals that the BS should employ a finite set of MA deployment patterns, each allocated an optimal time duration. Building on this, we then study the general case with limited MA movement speed and propose a heuristic trajectory design inspired by the optimal patterns identified in the ideal scenario. Several insights are also gained by examining the simplified special case. Finally, numerical results are provided to validate the effectiveness of the proposed designs compared to competitive benchmarks.

Problem

• movable antennas
• trajectory design
• rate fairness
• multiuser communications
• minimum achievable rate

Innovation

• movable antenna
• trajectory design
• rate fairness
• spatial reconfiguration
• multiuser communication