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Cell-Free MIMO with Rotatable Antennas: When Macro-Diversity Meets Antenna Directivity

Xingxiang Peng, Qingqing Wu, Ziyuan Zheng, Yanze Zhu, Wen Chen, Penghui Huang, Ying Gao, Honghao Wang

TL;DR

The paper tackles max-min fairness in downlink cell-free MIMO with rotatable antennas by formulating a joint beamforming and antenna-orientation optimization problem. It introduces an alternating-optimization framework where beamformers are found via SOCP-based bisection for fixed orientations and RA orientations are updated via SCA; a two-stage low-complexity variant uses a manifold-aware Frank-Wolfe step for orientation design followed by SOCP beamforming. Simulation results show that orientation-aware designs yield substantial improvements in the worst-user rate compared to beamforming-only baselines, with moderate steering ranges capturing most gains and the benefits increasing with antenna directivity only when orientations are properly aligned. The findings offer practical guidance for RA-enabled cell-free deployments, highlighting that carefully coordinated directivity and orientation control can significantly improve service uniformity and macro-diversity, while preserving computational feasibility through the proposed low-complexity two-stage method.

Abstract

Cell-free networks leverage distributed access points (APs) to achieve macro-diversity, yet their performance is often constrained by large disparities in channel quality arising from user geometry and blockages. To address this, rotatable antennas (RAs) add a lightweight hardware degree of freedom by steering the antenna boresight toward dominant propagation directions to strengthen unfavorable links, thereby enabling the network to better exploit macro-diversity for higher and more uniform performance. This paper investigates an RA-enabled cell-free downlink network and formulates a max-min rate problem that jointly optimizes transmit beamforming and antenna orientations. To tackle this challenging problem, we develop an alternating-optimization-based algorithm that iteratively updates the beamformers via a second-order cone program (SOCP) and optimizes the antenna orientations using successive convex approximation. To reduce complexity, we further propose an efficient two-stage scheme that first designs orientations by maximizing a proportional-fair log-utility using manifold-aware Frank-Wolfe updates, and then computes the beamformers using an SOCP-based design. Simulation results demonstrate that the proposed orientation-aware designs achieve a substantially higher worst-user rate than conventional beamforming-only benchmarks. Furthermore, larger antenna directivity enhances fairness with proper orientation but can degrade the worst-user performance otherwise.

Cell-Free MIMO with Rotatable Antennas: When Macro-Diversity Meets Antenna Directivity

TL;DR

The paper tackles max-min fairness in downlink cell-free MIMO with rotatable antennas by formulating a joint beamforming and antenna-orientation optimization problem. It introduces an alternating-optimization framework where beamformers are found via SOCP-based bisection for fixed orientations and RA orientations are updated via SCA; a two-stage low-complexity variant uses a manifold-aware Frank-Wolfe step for orientation design followed by SOCP beamforming. Simulation results show that orientation-aware designs yield substantial improvements in the worst-user rate compared to beamforming-only baselines, with moderate steering ranges capturing most gains and the benefits increasing with antenna directivity only when orientations are properly aligned. The findings offer practical guidance for RA-enabled cell-free deployments, highlighting that carefully coordinated directivity and orientation control can significantly improve service uniformity and macro-diversity, while preserving computational feasibility through the proposed low-complexity two-stage method.

Abstract

Cell-free networks leverage distributed access points (APs) to achieve macro-diversity, yet their performance is often constrained by large disparities in channel quality arising from user geometry and blockages. To address this, rotatable antennas (RAs) add a lightweight hardware degree of freedom by steering the antenna boresight toward dominant propagation directions to strengthen unfavorable links, thereby enabling the network to better exploit macro-diversity for higher and more uniform performance. This paper investigates an RA-enabled cell-free downlink network and formulates a max-min rate problem that jointly optimizes transmit beamforming and antenna orientations. To tackle this challenging problem, we develop an alternating-optimization-based algorithm that iteratively updates the beamformers via a second-order cone program (SOCP) and optimizes the antenna orientations using successive convex approximation. To reduce complexity, we further propose an efficient two-stage scheme that first designs orientations by maximizing a proportional-fair log-utility using manifold-aware Frank-Wolfe updates, and then computes the beamformers using an SOCP-based design. Simulation results demonstrate that the proposed orientation-aware designs achieve a substantially higher worst-user rate than conventional beamforming-only benchmarks. Furthermore, larger antenna directivity enhances fairness with proper orientation but can degrade the worst-user performance otherwise.
Paper Structure (16 sections, 3 theorems, 51 equations, 7 figures, 3 algorithms)

This paper contains 16 sections, 3 theorems, 51 equations, 7 figures, 3 algorithms.

Table of Contents

  1. Introduction
  2. System Model and Problem Formulation
  3. RA Model
  4. Channel Model
  5. Signal Model
  6. Problem Formulation
  7. Proposed AO-Based Solution
  8. Optimization of Beamformers
  9. Optimization of RA Orientations
  10. Overall Algorithm, Convergence, and Complexity
  11. Proposed Low-Complexity Solution
  12. Simulation Results and Discussions
  13. Convergence Behavior
  14. Performance Comparison
  15. Conclusion
  16. ...and 1 more sections

Key Result

Proposition 1

Suppose that the antenna directivity factor satisfies $p \ge 2$. Then, for each user $k$, there exists a finite constant $\xi_k>0$ such that $S_k$ admits the following global quadratic lower bound: where $\{\tilde{\bm f}_{b,m}^{[t]}\}$ denotes the current SCA iterate and is treated as fixed when constructing the surrogate function. Similarly, there exists a finite constant $\chi_k>0$ such that $I

Figures (7)

  • Figure 1: A cell-free MIMO network with rotatable antennas.
  • Figure 2: Network topology. Five APs are uniformly deployed on a circle with radius $R_{\text{cov}} = 300$ m. The $K = 8$ single-antenna users are uniformly distributed within the coverage disc.
  • Figure 3: The convergence behavior of the proposed AO-based algorithm.
  • Figure 4: The min-user rate vs. the maximum zenith angle.
  • Figure 5: The min-user rate vs. the transmit power budget per AP.
  • ...and 2 more figures

Theorems & Definitions (4)

  • Remark 1: Element-wise orientation vs. UPA pose control
  • Proposition 1: Surrogate functions for $S_k$ and $I_k$
  • Lemma 1: Diagonal scaling induced by normalization
  • Proposition 2: Monotone convergence of Algorithm \ref{['AO-Alg']}