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Performance Analysis of XL-MIMO with Rotary and Movable Antennas for High-speed Railway

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

TL;DR

This work addresses the challenge of dynamic XL-MIMO performance in high-speed railway environments by introducing ROMA (rotary and movable antennas) to adapt antenna spacing and 3D orientation. It develops a mobility-aware near-field beam-training-based localization, derives a channel-orthogonality condition from the spatial-correlation matrix, and provides an analytic antenna-spacing formula to achieve orthogonality. A differential-evolution algorithm optimizes the ROMA rotation angles to maximize the channel rank and thus capacity under train motion. Simulations at 20 GHz and 350 km/h demonstrate significant capacity gains for ROMA configurations over fixed-position setups, validating the framework's potential for robust, high-throughput HSR wireless links.

Abstract

The rotary and movable antennas (ROMA) technology is efficient in enhancing wireless network capacity by adjusting both the antenna spacing and three-dimensional (3D) rotation of antenna surfaces, based on the spatial distribution of users and channel statistics. Applying ROMA to high-speed rail (HSR) wireless communications can significantly improve system performance in terms of array gain and spatial multiplexing. However, the rapidly changing channel conditions in HSR scenarios present challenges for ROMA configuration. In this correspondence, we propose a analytical framework for configuring ROMA-based extremely large-scale multiple-input-multiple-output (XL-MIMO) system in HSR scenarios based on spatial correlation. First, we develop a localization model based on a mobility-aware near-field beam training algorithm to determine the real-time position of the train relay antennas. Next, we derive the expression for channel orthogonality and antenna spacing based on the spatial correlation matrix, and obtain the optimal antenna spacing when the transceiver panels are aligned in parallel. Moreover, we propose an optimization algorithm for the rotation angle of the transceiver panels, leveraging the differential evolution method, to determine the optimal angle. Finally, numerical results are provided to validate the computational results and optimization algorithm.

Performance Analysis of XL-MIMO with Rotary and Movable Antennas for High-speed Railway

TL;DR

This work addresses the challenge of dynamic XL-MIMO performance in high-speed railway environments by introducing ROMA (rotary and movable antennas) to adapt antenna spacing and 3D orientation. It develops a mobility-aware near-field beam-training-based localization, derives a channel-orthogonality condition from the spatial-correlation matrix, and provides an analytic antenna-spacing formula to achieve orthogonality. A differential-evolution algorithm optimizes the ROMA rotation angles to maximize the channel rank and thus capacity under train motion. Simulations at 20 GHz and 350 km/h demonstrate significant capacity gains for ROMA configurations over fixed-position setups, validating the framework's potential for robust, high-throughput HSR wireless links.

Abstract

The rotary and movable antennas (ROMA) technology is efficient in enhancing wireless network capacity by adjusting both the antenna spacing and three-dimensional (3D) rotation of antenna surfaces, based on the spatial distribution of users and channel statistics. Applying ROMA to high-speed rail (HSR) wireless communications can significantly improve system performance in terms of array gain and spatial multiplexing. However, the rapidly changing channel conditions in HSR scenarios present challenges for ROMA configuration. In this correspondence, we propose a analytical framework for configuring ROMA-based extremely large-scale multiple-input-multiple-output (XL-MIMO) system in HSR scenarios based on spatial correlation. First, we develop a localization model based on a mobility-aware near-field beam training algorithm to determine the real-time position of the train relay antennas. Next, we derive the expression for channel orthogonality and antenna spacing based on the spatial correlation matrix, and obtain the optimal antenna spacing when the transceiver panels are aligned in parallel. Moreover, we propose an optimization algorithm for the rotation angle of the transceiver panels, leveraging the differential evolution method, to determine the optimal angle. Finally, numerical results are provided to validate the computational results and optimization algorithm.

Paper Structure

This paper contains 8 sections, 1 theorem, 30 equations, 4 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model
  3. ROMA-HSR XL-MIMO Systems
  4. Localization Model
  5. Channel Correlation Model
  6. Differential Evolution Algorithm for ROMA
  7. Simulation Results and Discussions
  8. Conclusion

Key Result

Corollary 1

When the transceiver planes are parallel and the antenna spacing is uniform with $\alpha_1,\beta_1,\alpha_2,\beta_2=0$ and $d_{th}=d_{tv}=d_{rh}=d_{rv}=d$, the antenna spacing can be expressed as

Figures (4)

  • Figure 1: ROMA-enabled HSR XL-MIMO communication systems.
  • Figure 2: Localization NMSE against the antenna number of the transmitter and receiver with different near-field beam train algorithms.
  • Figure 3: Capacity versus normalized antenna spacing for different antenna numbers, physical distances and carrier frequencies.
  • Figure 4: Normalized channel capacity versus the $x$-axis location for three cases: parallel receiver and transmitter with FPA, one-sided plane with ROMA, and both planes with ROMA.

Theorems & Definitions (2)

  • Corollary 1
  • Remark 1