Spatial Consistency Evaluation Based on Massive SIMO Measurements

TL;DR

This paper assesses the spatial consistency of massive SIMO channels in small cell scenarios using covariance matrix similarity, revealing its strong environmental dependence and limitations of current models.

Contribution

It introduces a measurement-based evaluation method for spatial consistency and classifies measurement tracks, highlighting environmental factors over large-scale parameters.

Findings

Spatial consistency varies significantly with environment.

Correlation matrix distance effectively measures similarity.

Current 3GPP models inadequately capture spatial consistency.

Abstract

In this paper, the spatial consistency of wireless massive single-input-multiple-output channels in a cellular small cell scenario is evaluated based on measurements taken in Berlin city. The evaluation is done by computing the similarity of covariance matrices over the distance. As similarity measure the correlation matrix distance is used. A classification of the measurements tracks based on the shape of the curves into four different categories is done. The results in this paper indicate that spatial consistency is a highly deterministic property in the sense that it depends strongly on the individual environment and not so much on large scale parameters. Therefore, we conclude that spatial consistency is not sufficiently modelled by the current 3rd Generation Partnership Project feature.