Distributed Near-Field Channel Estimation for U6G XL-MIMO Systems under Beam Squint

TL;DR

This paper introduces a distributed parametric symmetry-based algorithm for efficient wideband near-field channel estimation in U6G XL-MIMO systems, effectively reducing complexity and pilot overhead under beam squint effects.

Contribution

It proposes a novel distributed estimation method leveraging channel parameter symmetry, eliminating the need for polar-domain scanning, and reducing pilot and computational requirements.

Findings

Higher estimation accuracy demonstrated in simulations

Reduced complexity and pilot overhead compared to existing methods

Effective under beam squint and near-field effects in U6G XL-MIMO

Abstract

Since the beam squint and near-field effects both inherently exist in upper-6 GHz (U6G) extremely large-scale multiple-input multiple-output (XL-MIMO) systems, wideband near-field channel estimation faces severe challenges, such as higher computational complexity, and higher pilot overhead particularly at hybrid architectures with fewer radio frequency (RF) chains. To precisely reduce the complexity and number of pilots, the parametric symmetry of wideband near-field channels is explored, such that the channel parameters, including angle, distance, and range, can be decoupled based on the delay variations observed by different antennas. Based on this, a distributed parametric symmetry-based (DPS) algorithm, applicable to U6G XL-MIMO, is proposed. The delays observed by different subarrays are estimated and extrapolated across the local processing units (LPUs) firstly, and then, the channel parameters are decoupled and estimated at the central processing unit (CPU), by only linearly combining the delays from different LPUs. The path gains are calculated at different LPUs, respectively, to reconstruct the channel with low complexity. Since the proposed algorithm does not rely on scanning the polar-domain dictionary, only a single pilot is required even with hybrid architectures. Furthermore, the computational complexity, multiple-path resolution, Cramer-Rao lower bound (CRLB) and lower bound (LB) of the estimates in hybrid architectures and the DPS algorithm, respectively, are analyzed, to evaluate the realizable potential of the proposed algorithm. The simulation results prove that the proposed algorithm has a higher estimation accuracy, while requiring less complexity and pilots.