Chartwin: a Case Study on Channel Charting-aided Localization in Dynamic Digital Network Twins

TL;DR

This paper introduces Chartwin, a semi-supervised channel charting method integrated with digital network twins, achieving sub-10 meter localization accuracy in dynamic urban environments.

Contribution

It presents a novel case study on combining channel charting with dynamic digital network twins for improved localization accuracy.

Findings

Achieves approximately 4.5 m localization error in static DNTs.

Achieves approximately 6 m localization error in dynamic DNTs.

Demonstrates the effectiveness of semi-supervised channel charting in urban environments.

Abstract

Wireless communication systems can significantly benefit from the availability of spatially consistent representations of the wireless channel to efficiently perform a wide range of communication tasks. Towards this purpose, channel charting has been introduced as an effective unsupervised learning technique to achieve both locally and globally consistent radio maps. In this letter, we propose Chartwin, a case study on the integration of localization-oriented channel charting with dynamic Digital Network Twins (DNTs). Numerical results showcase the significant performance of semi-supervised channel charting in constructing a spatially consistent chart of the considered extended urban environment. The considered method results in $\approx$ 4.5 m localization error for the static DNT and $\approx$ 6 m in the dynamic DNT, fostering DNT-aided channel charting and localization.