# Wireless Channel Charting: Theory, Practice, and Applications

arXiv: https://arxiv.org/abs/2304.08095 · HTML: https://mlsanity.com/paper/2304.08095/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 16 references that are in the map.
- First posted on arXiv 17 Apr 2023.

## Builds on (most cited first, 4 of 4)

- [Channel Charting: Locating Users within the Radio Environment using Channel State Information](https://mlsanity.com/paper/1807.05247/) (2018)
- [Triplet-Based Wireless Channel Charting: Architecture and Experiments](https://mlsanity.com/paper/2005.12242/) (2020)
- [6G White Paper on Localization and Sensing](https://mlsanity.com/paper/2006.01779/) (2020)
- [Kernel-Based Adaptive Online Reconstruction of Coverage Maps With Side Information](https://mlsanity.com/paper/1404.0979/) (2014)

## Built on by (most cited first, 9 of 9)

- [Calibrating Wireless Ray Tracing for Digital Twinning using Local Phase Error Estimates](https://mlsanity.com/paper/2312.12625/) (2023)
- [Learning Latent Wireless Dynamics from Channel State Information](https://mlsanity.com/paper/2409.10045/) (2024)
- [Optimizing Multicarrier Multiantenna Systems for LoS Channel Charting](https://mlsanity.com/paper/2310.03762/) (2023)
- [AI-driven Wireless Positioning: Fundamentals, Standards, State-of-the-art, and Challenges](https://mlsanity.com/paper/2501.14970/) (2025)
- [Blind Construction of Angular Power Maps in Massive MIMO Networks](https://mlsanity.com/paper/2510.07071/) (2025)
- [Channel Charting in Smart Radio Environments](https://mlsanity.com/paper/2508.07305/) (2025)
- [Global Scale Self-Supervised Channel Charting with Sensor Fusion](https://mlsanity.com/paper/2405.04357/) (2024)
- [Towards Channel Charting Enhancement with Non-Reconfigurable Intelligent Surfaces](https://mlsanity.com/paper/2511.00919/) (2025)
- [The Vienna 4G/5G Drive-Test Dataset](https://mlsanity.com/paper/2603.02638/) (2026)

## Abstract (arXiv)

Channel charting is a recently proposed framework that applies dimensionality reduction to channel state information (CSI) in wireless systems with the goal of associating a pseudo-position to each mobile user in a low-dimensional space: the channel chart. Channel charting summarizes the entire CSI dataset in a self-supervised manner, which opens up a range of applications that are tied to user location. In this article, we introduce the theoretical underpinnings of channel charting and present an overview of recent algorithmic developments and experimental results obtained in the field. We furthermore discuss concrete application examples of channel charting to network- and user-related applications, and we provide a perspective on future developments and challenges as well as the role of channel charting in next-generation wireless networks.