Directional Sparsity Based Statistical Channel Estimation for 6D Movable Antenna Communications

Shao X, Zhang R, Park J, Quek TQ, Schober R, Shen XS (2025)

Publication Type: Conference contribution

Publication year: 2025

Journal

2012 IEEE International Conference on Communications (ICC) Institute of Electrical and Electronics Engineers (IEEE)

Publisher: Institute of Electrical and Electronics Engineers Inc.

Pages Range: 5115-5120

Conference Proceedings Title: IEEE International Conference on Communications

Event location: Montreal, QC, CAN

ISBN: 9798331505219

DOI: 10.1109/ICC52391.2025.11161114

Abstract

Six-dimensional movable antenna (6DMA) is an innovative and transformative technology to improve wireless network capacity by adjusting the 3D positions and 3D rotations of antennas/surfaces (sub-arrays) based on the channel spatial distribution. For optimization of the antenna positions and rotations, the acquisition of statistical channel state information (CSI) is essential for 6DMA systems. In this paper, we unveil for the first time a new directional sparsity property of the 6DMA channels between the base station (BS) and the distributed users, where each user has significant channel gains only with a (small) subset of 6DMA position-rotation pairs, which can receive direct/reflected signals from the user. By exploiting this property, a covariance-based algorithm is proposed for estimating the statistical CSI in terms of the average channel power at a small number of 6DMA positions and rotations. Based on such limited channel power estimation, the average channel powers for all possible 6DMA positions and rotations in the BS movement region are reconstructed by further estimating the multi-path average power and direction-of-arrival (DOA) vectors of all users. Simulation results show that the proposed directional sparsitybased algorithm can achieve higher channel power estimation accuracy than existing benchmark schemes, while requiring a lower pilot overhead.

Authors with CRIS profile

Robert Schober Lehrstuhl für Digitale Übertragung (IDC)

Involved external institutions

University of Waterloo (UW) CA Canada (CA) The Chinese University of Hong Kong (CUHK) CN China (CN) National University of Singapore (NUS) SG Singapore (SG)

How to cite

APA:

Shao, X., Zhang, R., Park, J., Quek, T.Q., Schober, R., & Shen, X.S. (2025). Directional Sparsity Based Statistical Channel Estimation for 6D Movable Antenna Communications. In Matthew Valenti, David Reed, Melissa Torres (Eds.), IEEE International Conference on Communications (pp. 5115-5120). Montreal, QC, CAN: Institute of Electrical and Electronics Engineers Inc..

MLA:

Shao, Xiaodan, et al. "Directional Sparsity Based Statistical Channel Estimation for 6D Movable Antenna Communications." Proceedings of the 2025 IEEE International Conference on Communications, ICC 2025, Montreal, QC, CAN Ed. Matthew Valenti, David Reed, Melissa Torres, Institute of Electrical and Electronics Engineers Inc., 2025. 5115-5120.

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