Channel Estimation for Extremely Large-Scale Massive MIMO Systems

TLDR

Extremely large‑scale massive MIMO promises high‑capacity mobile communications, yet its huge aperture arrays introduce near‑field and spatial non‑stationary channel conditions that necessitate new transceiver designs and channel state information acquisition. This letter addresses the channel estimation problem by modeling the non‑stationary channel as a mapping between subarrays and scatterers. The authors propose subarray‑wise and scatterer‑wise estimation methods that view the near‑field channel from the perspectives of subarrays and scatterers, respectively. Numerical results show that the subarray‑wise method achieves accurate channel estimates with low complexity, while the scatterer‑wise method precisely locates scatterers and recovers almost all subarray‑scatterer mappings.

Abstract

Extremely large-scale massive multiple-input multiple-output has shown considerable potential in future mobile communications. However, the use of extremely large aperture arrays will lead to near-field and spatial non-stationary channel conditions, which result in changes in transceiver design and channel state information acquisition. This letter focuses on the channel estimation problem and describes the non-stationary channel through a mapping between subarrays and scatterers. We propose subarray-wise and scatterer-wise channel estimation methods to estimate the near-field non-stationary channel from the views of the subarray and the scatterer, respectively. Numerical results demonstrate that the subarray-wise method can derive accurate channel estimation results with low complexity, whereas the scatterer-wise method can accurately position the scatterers and identify almost all the mappings between subarrays and scatterers.