# Positioning Using Wireless Networks: Applications, Recent Progress and Future Challenges

arXiv: https://arxiv.org/abs/2403.11417 · HTML: https://mlsanity.com/paper/2403.11417/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Mar 2024.

## Built on by (most cited first, 8 of 8)

- [AI-driven Wireless Positioning: Fundamentals, Standards, State-of-the-art, and Challenges](https://mlsanity.com/paper/2501.14970/) (2025)
- [Analogical Learning for Cross-Scenario Generalization: Framework and Application to Intelligent Localization](https://mlsanity.com/paper/2504.08811/) (2025)
- [Multi-modal Data based Semi-Supervised Learning for Vehicle Positioning](https://mlsanity.com/paper/2410.20680/) (2024)
- [Conformal Prediction for Indoor Positioning with Correctness Coverage Guarantees](https://mlsanity.com/paper/2505.01810/) (2025)
- [On the Application of Deep Learning for Precise Indoor Positioning in 6G](https://mlsanity.com/paper/2410.19436/) (2024)
- [Improving Outdoor Multi-cell Fingerprinting-based Positioning via Mobile Data Augmentation](https://mlsanity.com/paper/2509.19405/) (2025)
- [Visible Light Positioning With Lam'e Curve LEDs: A Generic Approach for Camera Pose Estimation](https://mlsanity.com/paper/2602.01577/) (2026)
- [RA-LWLM: Retrieval-Augmented In-Context Localization with Wireless Foundation Models](https://mlsanity.com/paper/2606.01899/) (2026)

## Abstract (arXiv)

Positioning has recently received considerable attention as a key enabler in emerging applications such as extended reality, unmanned aerial vehicles and smart environments. These applications require both data communication and high-precision positioning, and thus they are particularly well-suited to be offered in wireless networks (WNs). The purpose of this paper is to provide a comprehensive overview of existing works and new trends in the field of positioning techniques from both the academic and industrial perspectives. The paper provides a comprehensive overview of positioning in WNs, covering the background, applications, measurements, state-of-the-art technologies and future challenges. The paper outlines the applications of positioning from the perspectives of public facilities, enterprises and individual users. We investigate the key performance indicators and measurements of positioning systems, followed by the review of the key enabler techniques such as artificial intelligence/large models and adaptive systems. Next, we discuss a number of typical wireless positioning technologies. We extend our overview beyond the academic progress, to include the standardization efforts, and finally, we provide insight into the challenges that remain. The comprehensive overview of exisitng efforts and new trends in the field of positioning from both the academic and industrial communities would be a useful reference to researchers in the field.