Double-Side Near-Field Channel Estimation for Extremely Large-Scale MIMO System

Abstract

Accurate channel estimation is essential to empower extremely large-scale MIMO (XL-MIMO) in 6G networks with ultra-high spectral efficiency. Unfortunately, most of the existing channel estimation methods designed for XL-MIMO fail to consider a double-side near-field scenario, where both transmitter and receiver are equipped with extremely large-scale antenna arrays. The existing channel estimation schemes cannot be directly applied to the double-side near-field scenario. In this paper, based on this scenario, we first derive double-side near-field Rayleigh distance (DS-RD) and effective doubleside near-field Rayleigh distance (EDS-RD) to determine the range of the double-side near-field region.Then, a double-side near-field channel model is proposed to match this scenario, where the distance of the transmitter from the receiver is smaller than EDS-RD. In the proposed channel model, the line of sight (LoS) path component is modeled by the geometric free assumption while non-line of sight (NLoS) path components are modeled by the near-field array response vectors. Finally, a double-side near-field channel estimation algorithm is proposed to solve the channel estimation problem in this scenario, where the LoS path component and NLoS path components are estimated separately. Numerical simulation results demonstrate that, the proposed channel estimation algorithm is able to outperform the existing methods.