A 3D Non-Stationary Channel Model for 6G Wireless Systems Employing Intelligent Reflecting Surfaces with Practical Phase Shifts

TL;DR

This paper introduces a 3D non-stationary channel model for 6G systems with IRS, accounting for practical phase shifts and mobility, and analyzes its statistical properties and effects on channel correlation.

Contribution

It proposes a novel 3D stochastic channel model for IRS-assisted MIMO systems that includes practical discrete phase shifts and mobility, advancing realistic channel simulation.

Findings

IRS enhances channel separation and increases time autocorrelation.

Discrete phase shifts impact the channel's temporal correlation compared to continuous shifts.

The model verifies non-stationary properties in IRS-assisted channels.

Abstract

In this paper, a three-dimensional (3D) geometry based stochastic model (GBSM) for a massive multiple-input multiple-output (MIMO) communication system employing practical discrete intelligent reflecting surface (IRS) is proposed. The proposed channel model supports the scenario where both transceivers and environments move. The evolution of clusters in the space domain and the practical discrete phase shifts are considered in the channel model. The steering vector is set at the base station for the cooperation with IRS. Through studying statistical properties, the non-stationary properties are verified. We find that IRS plays a role in separating the whole channel and make the absolute value of time autocorrelation function (ACF) larger than the situation without employing IRS. Time ACF of the case using discrete phase shifts is also compared with the continuous case.