Extremely large-scale multiple input multiple output (XL-MIMO), a key technology for 6G communications, faces challenges in near-field channel estimation due to spherical wavefronts and the need for three-dimensional (3D) spatial characterization, particularly with uniform circular arrays (UCAs). This letter proposes a spherical-domain simultaneous orthogonal matching pursuit (S-SOMP) based scheme tailored for near-field 3D channel estimation in UCA-equipped XL-MIMO systems. We establish a sparse channel representation based on the near-field spherical wave model. Then, a novel spherical-domain transform matrix codebook is designed via joint discrete sampling of distance, azimuth, and elevation parameters, leveraging analytical approximations to ensure low correlation between steering vectors. This structured codebook enables accurate sparse signal recovery using the S-SOMP algorithm for efficient joint estimation of channel path gains, spatial angles, and distances. Simulation results demonstrate significant channel estimation accuracy improvements compared to existing benchmarks.
@article{arxiv.2507.03507,
title = {Near-Field Codebook-Based 3D Spherical Channel Estimation for UCA XL-MIMO Systems},
author = {Chenliang Yang and Guangchi Zhang and Miao Cui and Qingqing Wu and Yong Zeng},
journal= {arXiv preprint arXiv:2507.03507},
year = {2025}
}