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ROMA: ROtary and Movable Antenna

Jiayi Zhang, Wenhui Yi, Bokai Xu, Zhe Wang, Huahua Xiao, Bo Ai

TL;DR

The study tackles spectral efficiency limitations of fixed-position MIMO by introducing ROMA, which combines rotary and movable antenna panels to enable 3D reconfiguration of both panel rotation and element locations. It develops an AO framework to jointly optimize rotation angles and element placements at both transmitter and receivers under MR/MIMO precoding, transforming non-convex subproblems with penalty-based and geometric approaches. Results show substantial average SE gains over baselines such as MA, RO, and AS, with larger improvements as the movable region and transmit power increase. This approach offers a practical path to significantly boost spatial degrees of freedom in downlink MU-MIMO without increasing antenna counts, enabling more flexible and efficient wireless systems.

Abstract

The rotary and movable antenna (ROMA) architecture represents a next-generation multi-antenna technology that enables flexible adjustment of antenna position and array rotation angles of the transceiver. In this letter, we propose a ROMA-aided multi-user MIMO communication system to fully enhance the efficiency and reliability of system transmissions. By deploying ROMA panels at both the transmitter and receiver sides, and jointly optimizing the three-dimensional (3D) rotation angles of each ROMA panel and the relative positions of antenna elements based on the spatial distribution of users and channel state information (CSI), we can achieve the objective of maximizing the average spectral efficiency (SE). Subsequently, we conduct a detailed analysis of the average SE performance of the system under the consideration of maximum ratio (MR) precoding. Due to the non-convexity of the optimization problem in the ROMA multi-user MIMO system, we propose an efficient solution based on an alternating optimization (AO) algorithm. Finally, simulation results demonstrate that the AO-based ROMA architecture can significantly improve the average SE. Furthermore, the performance improvement becomes more pronounced as the size of the movable region and the transmission power increase.

ROMA: ROtary and Movable Antenna

TL;DR

The study tackles spectral efficiency limitations of fixed-position MIMO by introducing ROMA, which combines rotary and movable antenna panels to enable 3D reconfiguration of both panel rotation and element locations. It develops an AO framework to jointly optimize rotation angles and element placements at both transmitter and receivers under MR/MIMO precoding, transforming non-convex subproblems with penalty-based and geometric approaches. Results show substantial average SE gains over baselines such as MA, RO, and AS, with larger improvements as the movable region and transmit power increase. This approach offers a practical path to significantly boost spatial degrees of freedom in downlink MU-MIMO without increasing antenna counts, enabling more flexible and efficient wireless systems.

Abstract

The rotary and movable antenna (ROMA) architecture represents a next-generation multi-antenna technology that enables flexible adjustment of antenna position and array rotation angles of the transceiver. In this letter, we propose a ROMA-aided multi-user MIMO communication system to fully enhance the efficiency and reliability of system transmissions. By deploying ROMA panels at both the transmitter and receiver sides, and jointly optimizing the three-dimensional (3D) rotation angles of each ROMA panel and the relative positions of antenna elements based on the spatial distribution of users and channel state information (CSI), we can achieve the objective of maximizing the average spectral efficiency (SE). Subsequently, we conduct a detailed analysis of the average SE performance of the system under the consideration of maximum ratio (MR) precoding. Due to the non-convexity of the optimization problem in the ROMA multi-user MIMO system, we propose an efficient solution based on an alternating optimization (AO) algorithm. Finally, simulation results demonstrate that the AO-based ROMA architecture can significantly improve the average SE. Furthermore, the performance improvement becomes more pronounced as the size of the movable region and the transmission power increase.
Paper Structure (7 sections, 2 theorems, 16 equations, 4 figures, 1 algorithm)

This paper contains 7 sections, 2 theorems, 16 equations, 4 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model
  3. Performance Analysis
  4. Proposed Algorithm
  5. Simulation Results
  6. Conclusion
  7. Proof of Theorem 1 and Corollary 1

Key Result

Theorem 1

When maximum ratio (MR) precodingThe boundedness of $SE_u$ can be similarly proven for other precoding schemes. is applied, the upper bound of $SE_u$ shown in SE can be expressed as: where $p_u$ is the transmit power to the $u$-th user, the channel gain $\left\| \mathbf{H}_u \right\| _{F}^{2}\leq\sum_{m=1}^M{\sum_{n_u=1}^{N_u}{\left\| \mathbf{b}_{umn_u} \right\| _{1}^{2}}}$$=G_u$, and the Inter-u

Figures (4)

  • Figure 1: ROMA-aided multi-user MIMO communication system.
  • Figure 2: Average SE versus the number of iterations for different optimization algorithms with different transmit power $p$.
  • Figure 3: Average SE versus the normalized region size $A$ for different system architectures with $p = 30~\mathrm{dBm}$.
  • Figure 4: Average SE versus the transmit power $p$ for different system architectures with $A = 2.5 \lambda$.

Theorems & Definitions (2)

  • Theorem 1
  • Corollary 1