Near-Field Channel Estimation in Mixed LoS/NLoS Environments for Extremely Large-Scale MIMO Systems
Yu Lu, and Linglong Dai

TL;DR
This paper introduces a near-field channel model for XL-MIMO systems in mixed LoS/NLoS environments, along with a two-stage estimation algorithm that outperforms existing methods in accuracy.
Contribution
It proposes a novel mixed LoS/NLoS near-field XL-MIMO channel model and a two-stage estimation algorithm with derived CRLB, addressing the limitations of existing models.
Findings
The proposed model accurately captures near-field effects in XL-MIMO.
The two-stage estimation algorithm outperforms existing methods.
CRLB analysis validates the algorithm's efficiency.
Abstract
Accurate channel model and channel estimation are essential to empower extremely large-scale MIMO (XL-MIMO) in 6G networks with ultra-high spectral efficiency. With the sharp increase in the antenna array aperture of the XL-MIMO scenario, the electromagnetic propagation field will change from far-field to near-field. Unfortunately, due to the near-field effect, most of the existing XL-MIMO channel models fail to describe mixed line-of-sight (LoS) and non-line-of-sight (NLoS) path components simultaneously. In this paper, a mixed LoS/NLoS near-field XL-MIMO channel model is proposed to match the practical near-field XL-MIMO scenario, where the LoS path component is modeled by the geometric free space propagation assumption while NLoS path components are modeled by the near-field array response vectors. Then, to define the range of near-field for XL-MIMO, the MIMO Rayleigh distance…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization · Energy Harvesting in Wireless Networks · Antenna Design and Analysis
