Pose-aware 3D Beamwidth Adaptation for Mobile Extended Reality

TL;DR

This paper introduces a pose-aware beamwidth adaptation method for XR HMDs that improves coverage and power efficiency by leveraging pose estimation correlations to adapt antenna beamwidth dynamically.

Contribution

It proposes a novel beamwidth adaptation scheme that uses estimation covariance to enhance coverage and efficiency in XR HMD communication.

Findings

Coverage area increased by approximately 16%

Power efficiency improved up to 18%

Leverages estimation correlations for better beam adaptation

Abstract

This paper presents a sensor-aided pose-aware beamwidth adaptation design for a conceptual extended reality (XR) Head-Mounted Display (HMD) equipped with a 2D planar array. The beam is tracked and adapted on the user side by leveraging HMD orientation estimates. The beamwidth adaptation scheme is effected by selective deactivation of elements in the 2D antenna array, employing the angular estimation covariance matrix to overlap the beam with the estimation confidence interval. The proposed method utilizes the estimation correlations to adapt the beamwidth along the confidence interval of these estimates. Compared to a beamwidth adaptation without leveraging estimation correlations, the proposed method demonstrates the gain of leveraging estimation correlations by improving the coverage area for a given outage probability threshold by approximately 16%, or equivalently increasing the power efficiency up to 18%.