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Weighted Sum-Rate Maximization for Movable Antenna-Enhanced Wireless Networks

Biqian Feng, Yongpeng Wu, Xiang-Gen Xia, Chengshan Xiao

TL;DR

This work tackles weighted sum-rate maximization in downlink networks with movable antennas (MAs) at both the BS and users. It reformulates the nonconvex problem as a $WMMSE$ problem and solves it via block coordinate descent, integrating MM-based antenna-position updates and a planar movement mode to reduce complexity. The proposed method achieves significant $WSR$ gains over traditional fixed-antenna systems, with the planar movement mode offering roughly a 30% reduction in computation time while incurring only small performance loss. The results underscore the practical potential of MA-enabled MIMO to enhance spectral efficiency in future wireless networks.

Abstract

This letter investigates the weighted sum rate maximization problem in movable antenna (MA)-enhanced systems. To reduce the computational complexity, we transform it into a more tractable weighted minimum mean square error (WMMSE) problem well-suited for MA. We then adopt the WMMSE algorithm and majorization-minimization algorithm to optimize the beamforming and antenna positions, respectively. Moreover, we propose a planar movement mode, which constrains each MA to a specified area, we obtain a low-complexity closed-form solution. Numerical results demonstrate that the MA-enhanced system outperforms the conventional system. Besides, the computation time for the planar movement mode is reduced by approximately 30\% at a little performance expense.

Weighted Sum-Rate Maximization for Movable Antenna-Enhanced Wireless Networks

TL;DR

This work tackles weighted sum-rate maximization in downlink networks with movable antennas (MAs) at both the BS and users. It reformulates the nonconvex problem as a problem and solves it via block coordinate descent, integrating MM-based antenna-position updates and a planar movement mode to reduce complexity. The proposed method achieves significant gains over traditional fixed-antenna systems, with the planar movement mode offering roughly a 30% reduction in computation time while incurring only small performance loss. The results underscore the practical potential of MA-enabled MIMO to enhance spectral efficiency in future wireless networks.

Abstract

This letter investigates the weighted sum rate maximization problem in movable antenna (MA)-enhanced systems. To reduce the computational complexity, we transform it into a more tractable weighted minimum mean square error (WMMSE) problem well-suited for MA. We then adopt the WMMSE algorithm and majorization-minimization algorithm to optimize the beamforming and antenna positions, respectively. Moreover, we propose a planar movement mode, which constrains each MA to a specified area, we obtain a low-complexity closed-form solution. Numerical results demonstrate that the MA-enhanced system outperforms the conventional system. Besides, the computation time for the planar movement mode is reduced by approximately 30\% at a little performance expense.
Paper Structure (13 sections, 2 theorems, 28 equations, 4 figures)

This paper contains 13 sections, 2 theorems, 28 equations, 4 figures.

Table of Contents

  1. Introduction
  2. System Model
  3. Field-Response-Based Channel Model
  4. Problem Formulation
  5. Block Coordinate Descent Method for MA-Enhanced Multiuser MIMO System
  6. Transceiver Beamformer Design
  7. MA Position Design at BS
  8. MA Position Design at Users
  9. Low-Complexity Design
  10. Planar Movement Mode at BS
  11. Convergence and Complexity Analysis
  12. Numerical Results
  13. Conclusion

Key Result

Lemma 1

The quadratic form $\mathbf x^H \mathbf L \mathbf x$, where $\mathbf L$ is a Hermitian matrix, can be upper bounded as MM: where $\mathbf M\succeq\mathbf L$. Equality is achieved at $\mathbf x = \mathbf x_0$.

Figures (4)

  • Figure 1: System model: an MA-enhanced multiuser MIMO system.
  • Figure 2: Convergence of the proposed algorithms.
  • Figure 3: Evaluation of weighted sum rate under different number of antennas $M$.
  • Figure 4: Evaluation of weighted sum rate under different minimum inter-MA distance $D$.

Theorems & Definitions (2)

  • Lemma 1
  • Lemma 2