Channel Estimation for Near-Field Line-of-Sight XL-MIMO Communications Using Geometric Prior

This letter investigates the channel estimation for near-field line-of-sight (LoS) extremely-large multiple-input-multiple-output (XL-MIMO) communications, where both the transceivers are equipped with uniform linear arrays (ULAs). For near-field LoS channels within millimeter wave and sub-teraherz frequency bands, electromagnetic waves typically propagate with little diffraction or scattering, implying the propagation direction of each plane-wave component remains almost invariant under the Fourier plane-wave series expansion. This invariance indicates a strong correlation between the propagation directions of transmitted and received plane-wave components, called geometric prior in this letter. Initially, we utilize the wavenumber-domain sparsifying basis to decompose the channel into several plane-wave components. Then, we deduce the potential locations of non-zero entries in the wavenumber-domain channel matrix for any relative orientation angle between the ULAs. Subsequently, a two-stage channel estimation framework is further proposed. Specifically, the first stage aims to derive the orientation angle, and the second stage performs compressed sensing within a reduced search space. Simulation results are provided to validate the robustness of our proposed angle and channel estimation.

I. Introduction

Within millimeter wave (mmWave) and sub-terahertz (sub-THz) frequency bands, the path loss of non-line-of-sight (NLoS) propagation is typically much greater than that of line-of-sight (LoS) propagation, due to the weak reflection and diffraction ability of high-frequency electromagnetic (EM) waves [1]. According to the 3GPP TS 38.901 standard, for mmWave communications in Urban Micro (UMi) scenarios, the LoS path loss typically ranges from 130 to 150 dB, whereas the NLoS path loss typically ranges from 160 to 180 dB [2]. Therefore, there is increasingly growing interest in LoS extremely-large (XL) multi-input-multi-output (MIMO) communications, such as the works described in [3], [4], [5], and [6].