Geometry-Based Stochastic Channel Models for 5G: Extending Key Features for Massive MIMO

TL;DR

This paper enhances geometry-based stochastic channel models for 5G massive MIMO by incorporating multi-user consistency, non-stationarities, and spherical wave effects, improving realism and applicability.

Contribution

It introduces novel features like user aura, sub-array non-stationarity, and spherical wave modeling to extend existing channel models for massive MIMO.

Findings

Enhanced MU consistency with user aura concept

Modeling of non-stationarities across large arrays

Inclusion of spherical wave effects for accuracy

Abstract

This paper introduces three key features in geometry-based stochastic channel models in order to include massive MIMO channels. Those key features consists of multi-user (MU) consistency, non-stationarities across the base station array and inclusion of spherical wave modelling. To ensure MU consistency, we introduce the concept of "user aura", which is a circle around the user with radius defined according to the stationarity interval. The overlap between auras determines the share of common clusters among users. To model non-stationarities across a massive array, sub-arrays are defined for which clusters are independently generated. At last, we describe a procedure to incorporate spherical wave modelling, where a cluster focal point is defined to account for distance between user and cluster.