Table of Contents
Fetching ...

Movable Antenna-Aided Hybrid Beamforming for Multi-User Communications

Yichi Zhang, Yuchen Zhang, Lipeng Zhu, Sa Xiao, Wanbin Tang, Yonina C. Eldar, Rui Zhang

TL;DR

The work develops movable-antenna aided multi-user hybrid beamforming with a sub-connected structure to maximize sum rate in downlink MU-MISO. It leverages fractional programming to reformulate the non-convex objective and an alternating-optimization framework to jointly optimize the digital beamformer ${\bf W}_{\rm D}$, analog beamformer ${\bf W}_{\rm A}$, and movable subarray positions ${\bf c}$ under unit-modulus and power constraints. The proposed algorithm combines Lagrange multipliers, a penalty method, and gradient descent to solve the resulting subproblems, achieving substantial gains over fixed-position designs and, with sufficiently large movable regions, outperforming fully-connected fixed-position arrays. This demonstrates the practical potential of movable antennas to enhance beamforming flexibility and system capacity in high-frequency wireless links.

Abstract

In this correspondence, we propose a movable antenna (MA)-aided multi-user hybrid beamforming scheme with a sub-connected structure, where multiple movable sub-arrays can independently change their positions within different local regions. To maximize the system sum rate, we jointly optimize the digital beamformer, analog beamformer, and positions of subarrays, under the constraints of unit modulus, finite movable regions, and power budget. Due to the non-concave/non-convex objective function/constraints, as well as the highly coupled variables, the formulated problem is challenging to solve. By employing fractional programming, we develop an alternating optimization framework to solve the problem via a combination of Lagrange multipliers, penalty method, and gradient descent. Numerical results reveal that the proposed MA-aided hybrid beamforming scheme significantly improves the sum rate compared to its fixed-position antenna (FPA) counterpart. Moreover, with sufficiently large movable regions, the proposed scheme with sub-connected MA arrays even outperforms the fully-connected FPA array.

Movable Antenna-Aided Hybrid Beamforming for Multi-User Communications

TL;DR

The work develops movable-antenna aided multi-user hybrid beamforming with a sub-connected structure to maximize sum rate in downlink MU-MISO. It leverages fractional programming to reformulate the non-convex objective and an alternating-optimization framework to jointly optimize the digital beamformer , analog beamformer , and movable subarray positions under unit-modulus and power constraints. The proposed algorithm combines Lagrange multipliers, a penalty method, and gradient descent to solve the resulting subproblems, achieving substantial gains over fixed-position designs and, with sufficiently large movable regions, outperforming fully-connected fixed-position arrays. This demonstrates the practical potential of movable antennas to enhance beamforming flexibility and system capacity in high-frequency wireless links.

Abstract

In this correspondence, we propose a movable antenna (MA)-aided multi-user hybrid beamforming scheme with a sub-connected structure, where multiple movable sub-arrays can independently change their positions within different local regions. To maximize the system sum rate, we jointly optimize the digital beamformer, analog beamformer, and positions of subarrays, under the constraints of unit modulus, finite movable regions, and power budget. Due to the non-concave/non-convex objective function/constraints, as well as the highly coupled variables, the formulated problem is challenging to solve. By employing fractional programming, we develop an alternating optimization framework to solve the problem via a combination of Lagrange multipliers, penalty method, and gradient descent. Numerical results reveal that the proposed MA-aided hybrid beamforming scheme significantly improves the sum rate compared to its fixed-position antenna (FPA) counterpart. Moreover, with sufficiently large movable regions, the proposed scheme with sub-connected MA arrays even outperforms the fully-connected FPA array.
Paper Structure (11 sections, 21 equations, 3 figures, 1 algorithm)

This paper contains 11 sections, 21 equations, 3 figures, 1 algorithm.

Figures (3)

  • Figure 1: MA-aided sub-connected hybrid beamforming structure.
  • Figure 2: Sum-rate versus $P_{max}$ with $D=2\lambda$.
  • Figure 3: Sum-rate versus the normalized region size with $P_{max}=10$ dBm.