Evaluation of the Spatial Consistency Feature in the 3GPP GSCM Channel Model

TL;DR

This paper evaluates the spatial consistency feature in the latest 3GPP GSCM channel model, which aims to improve the spatial correlation of small-scale fading for better MIMO and beamforming performance.

Contribution

It provides an assessment of the spatial consistency feature introduced in the latest 3GPP GSCM channel model, addressing previous limitations in spatial correlation modeling.

Findings

The spatial consistency feature improves the spatial correlation of small-scale fading.

The evaluation confirms the effectiveness of the new feature in the updated model.

Results support its use for more accurate MIMO and beamforming simulations.

Abstract

Since the development of 4G networks, Multiple-Input Multiple-Output (MIMO) and later multiple-user MIMO became a mature part to increase the spectral efficiency of mobile communication networks. An essential part of simultaneous multiple-user communication is the grouping of users with complementing channel properties. With the introduction of Base Station (BS) with large amount of antenna ports, i.e. transceiver units, the focus in spatial precoding is moved from uniform to heterogeneous cell coverage with changing traffic demands throughout the cell and 3D beamforming. In order to deal with the increasing feedback requirement for Frequency-Division Duplex (FDD) systems, concepts for user clustering on second order statistics are suggested in both the scientific and standardization literature. Former 3rd Generation Partnership Project (3GPP) Geometry-based Stochastic Channel Model (GSCM) channel models lack the required spatial correlation of small-scale fading. Since the latest release of 3GPP Geometry-based Stochastic Channel Model this issue is claimed to be solved and hence our contribution is an evaluation of this spatial consistency feature.