Robust beamforming and position optimization for movable antenna enabled 6G wireless communications

Journal on Advances in Signal Processing

卷:2026

Research

Yu Chen¹  Yongliang Sun¹ 

[1] College of Computer and Information Engineering, Nanjing Tech University, Puzhu South Road, 211816, Nanjing, Jiangsu, China

关键词: Movable antennas;    Channel state information error;    Robust precoding;    Orthogonal matching pursuit;    Monte Carlo methods;   

DOI  :  10.1186/s13634-026-01328-w

 received in 2026-01-29, accepted in 2026-04-13,  发布年份 2026

来源: Springer

【 摘 要 】

Although movable antenna (MA) systems offer significant performance gains via spatial reconfiguration, they suffer from severe degradation under practical imperfect channel state information (CSI). To address this, this paper proposes a robust joint design of antenna position optimization and precoding. We model stochastic errors in angular parameters and path gains and develop a Robust Monte Carlo Orthogonal Matching Pursuit (RMC-OMP) algorithm. The algorithm effectively suppresses pseudo-correlation peak interference caused by CSI errors through statistically averaging matching scores across multiple channel error realizations, while strictly ensuring the half-wavelength spacing constraint. Simulation results demonstrate that the RMC-OMP retains 85.6%\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$85.6\%$$\end{document} of the sum rate achievable with perfect CSI. This validates the proposed algorithm’s strong robustness for 6G MA systems.

【 授权许可】

CC BY-NC-ND   
© The Author(s) 2026

【 图 表 】

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