Movable Subarray-Aided Hybrid Beamforming for Near-Field Multiuser Communications

2026-05-08

AI Summary

This study addresses the challenge of jointly achieving hardware feasibility and full exploitation of near-field spatial degrees of freedom in hybrid beamforming for extremely large-scale MIMO systems operating in the radiative near field. To this end, this work proposes a movable subarray-assisted hybrid beamforming architecture that, for the first time, integrates reconfigurable antenna placement with beamforming design in a unified optimization framework. By jointly optimizing antenna positions and beamformers, the proposed approach effectively harnesses distance- and location-dependent near-field spatial degrees of freedom to enable precise beam focusing and enhanced interference suppression. Leveraging a hybrid planar–spherical wave channel model, an alternating optimization algorithm combining fractional programming, ADMM, and projected gradient ascent is developed. Simulation results demonstrate that the proposed scheme significantly outperforms conventional fixed-antenna baselines, yielding substantial gains in multiuser sum rate.

Abstract

Movable antenna (MA)-enabled near-field (NF) communications offer significant potential for 6G, yet existing designs often neglect the practical constraints of hybrid beamforming (HBF) for extremely large-scale MIMO (XL-MIMO). Conversely, MA-aided HBF frequently overlooks the rich NF degrees of freedom (DoFs). This paper proposes a movable subarray (MSA)-aided HBF architecture for NF multiuser systems, which strikes a strategic balance between hardware practicality and spatial flexibility. By coupling MSA movement with HBF, the proposed design simultaneously exploits NF distance-dependent and MSA position-dependent DoFs, enabling highly precise beamfocusing and superior interference mitigation. To alleviate the computational burden, a hybrid planar-spherical wave model is introduced for efficient channel approximation. Furthermore, an alternating optimization (AO) algorithm is developed by integrating fractional programming, the alternating direction method of multipliers (ADMM), and projected gradient ascent. Simulation results validate substantial sum-rate gains over fixedposition antenna (FPA) benchmarks.

Problem

• movable antenna
• near-field communications
• hybrid beamforming
• XL-MIMO
• degrees of freedom

Innovation

• movable subarray
• hybrid beamforming
• near-field communications
• XL-MIMO
• alternating optimization