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

arXiv: https://arxiv.org/abs/2508.09055 · HTML: https://mlsanity.com/paper/2508.09055/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 13 references that are in the map.
- First posted on arXiv 12 Aug 2025.

## Builds on (most cited first, 6 of 6)

- [CARLA: An Open Urban Driving Simulator](https://mlsanity.com/paper/1711.03938/) (2017)
- [Channel Charting: Locating Users within the Radio Environment using Channel State Information](https://mlsanity.com/paper/1807.05247/) (2018)
- [Learning Latent Wireless Dynamics from Channel State Information](https://mlsanity.com/paper/2409.10045/) (2024)
- [A Multi-Modal Simulation Framework to Enable Digital Twin-based V2X Communications in Dynamic Environments](https://mlsanity.com/paper/2303.06947/) (2023)
- [Semi-supervised t-SNE for Millimeter-wave Wireless Localization](https://mlsanity.com/paper/2111.13573/) (2021)
- [Localization in Digital Twin MIMO Networks: A Case for Massive Fingerprinting](https://mlsanity.com/paper/2403.09614/) (2024)

## Abstract (arXiv)

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 ≈ 4.5 m localization error for the static DNT and ≈ 6 m in the dynamic DNT, fostering DNT-aided channel charting and localization.