Dynamic Geometry-Based Stochastic Channel Modeling for Polarized MIMO Systems with Moving Scatterers

TL;DR

This paper develops a 4D stochastic geometry-based model for polarized MIMO channels with moving scatterers, incorporating a novel motion path model and closed-form correlation formulas to analyze channel behavior and capacity.

Contribution

Introduces a new 4D GBSM with a high-fidelity motion path model based on Brownian Motion and Von Mises Fisher distribution for polarized MIMO systems with moving scatterers.

Findings

Closed-form space-time correlation function derived

Channel capacity analyzed via Monte Carlo simulations

Impact of moving scatterers on MIMO performance evaluated

Abstract

This paper introduces a four-dimensional (4D) geometry-based stochastic model (GBSM) for polarized multiple-input multiple-output (MIMO) systems with moving scatterers. We propose a novel motion path model with high degrees of freedom based on the Brownian Motion (BM) random process for randomly moving scatterers. This model is capable of analyzing the effect of both deterministically and randomly moving scatterers on channel properties. The mixture of Von Mises Fisher (VMF) distribution is considered for scatterers resulting in a more general and practical model. The proposed motion path model is applied to the clusters of scatterers with the mixture of VMF distribution, and a closed form formula for calculating space time correlation function (STCF) is achieved, allowing the study of the behavior of channel correlation and channel capacity in the time domain with the presence of stationary and moving scatterers. To obtain numerical results for channel capacity, we employed Monte Carlo simulation method for channel realization purpose. The impact of moving scatterers on the performance of polarized MIMO systems is evaluated using 2 by 2 MIMO configurations with various dual polarizations, i.e. V/V, V/H, and slanted 45{\deg} polarizations for different signal-to-noise (SNR) regimes. The proposed motion path model can be applied to study various dynamic systems with moving objects. The presented process and achieved formula are general and can be applied to polarized MIMO systems with any arbitrary number of antennas and polarizations.