Near-Field Codebook-Based 3D Spherical Channel Estimation for UCA XL-MIMO Systems

TL;DR

This paper introduces a novel near-field 3D channel estimation method for UCA-based XL-MIMO systems using a spherical-domain codebook and S-SOMP algorithm, significantly improving accuracy in spherical wavefront scenarios.

Contribution

It proposes a spherical-domain codebook and a S-SOMP based scheme for accurate near-field 3D channel estimation in UCA XL-MIMO systems, addressing spherical wavefront challenges.

Findings

Enhanced channel estimation accuracy over benchmarks

Effective joint estimation of angles, distances, and gains

Low correlation in the structured codebook

Abstract

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.