Fast and Robust Channel Estimation for HMIMO: A Graph-Based Wavenumber-Domain Approach

Xufeng Guo ¹Yuanbin Chen ²Ying Wang ¹Zhaocheng Wang ³Zhu Han ⁴Chau Yuen²

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作者信息

1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China
2. School of Electrical and Electronics Engineering, Nanyang Technological University, Jurong West, Singapore
3. Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China
4. Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA|Department of Computer Science and Engineering, Kyung Hee University, Seoul, South Korea
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Abstract

This paper proposes a fast and robust graph-based wavenumber-domain approach for channel estimation in holographic MIMO (HMIMO) systems. Unlike conventional angular-domain methods—prone to mutual coupling, power leakage, and sampling redundancy—our framework resolves HMIMO’s high-dimensional challenges by introducing a wavenumber-domain basis via orthogonal Fourier harmonics (FHs), eliminating dependencies on antenna density. By reformulating channel estimation as its sparse recovery counterpart, we model clustered sparsity using an elliptic Markov random field (EMRF), upon which a graph-cut swap expansion (GCSE) algorithm is developed, leveraging graph-theoretic optimizations for fast convergence and low complexity. Simulations demonstrate that our method achieves robust performance against mutual coupling, varying SNRs, and antenna density with drastically less computing time.

Key words

Channel estimation/Antennas/Radio frequency/Mutual coupling/Antenna arrays/Clustering algorithms/Probes/Feeds/Costs/Compressed sensing

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出版年

2025

IEEE transactions on wireless communications

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参考文献量65

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