MmWave for Extended Reality: Open User Mobility Dataset, Characterisation, and Impact on Link Quality

TL;DR

This paper presents a new dataset and analysis of high-mobility XR scenarios to understand their impact on mmWave link quality, aiding future wireless system design and mobility modeling.

Contribution

It introduces a comprehensive, publicly available dataset of high-mobility XR user data and characterizes its impact on mmWave link quality, filling a gap in existing research.

Findings

Mobility significantly affects mmWave link reliability.

Statistical models can approximate XR mobility patterns.

The dataset enables improved wireless system testing.

Abstract

User mobility in extended reality (XR) can have a major impact on millimeter-wave (mmWave) links and may require dedicated mitigation strategies to ensure reliable connections and avoid outage. The available prior art has predominantly focused on XR applications with constrained user mobility and limited impact on mmWave channels. We have performed dedicated experiments to extend the characterisation of relevant future XR use cases featuring a high degree of user mobility. To this end, we have carried out a tailor-made measurement campaign and conducted a characterisation of the collected tracking data, including the approximation of the data using statistical distributions. Moreover, we have provided an interpretation of the possible impact of the recorded mobility on mmWave technology. The dataset is made publicly accessible to provide a testing ground for wireless system design and to enable further XR mobility modelling.