Positioning for 5G

5G positioning at a Glance

5G stands for high data rates, low latency, high reliability, and pervasive connectivity - key enablers for applications such as IoT, V2X, and XR. Beyond communication, 5G also supports more efficient real-time location systems (RTLS): positions can be captured with high accuracy and used to optimize processes, for example in automated material supply with autonomous mobile robots (AMRs).

5G positioning is an integral part of 5G and is relevant across a wide range of application domains, including Industry and Logistics 4.0, logistics 4.0, smart city, medicine and health and rescue services..

This page provides an overview of key application areas, selected technologies, and suitable test and validation options for 5G-based localization at Fraunhofer IIS.

What does 5G positioning at Fraunhofer IIS mean?

5G positioning refers to the precise determination of positions and movements using cellular networks. It builds on 5G radio signals and the network architecture, which can support reliable positioning even in complex environments.

At Fraunhofer IIS, the focus is on developing and evaluating algorithms for 5G positioning. A current priority is combining AI methods with 5G positioning to make approaches more robust, more efficient, and easier to integrate into real-world applications. The work is conducted as applied research: the goal is to study positioning methods under realistic conditions and to translate their performance into concrete deployment scenarios—across campus and public networks as well as in industrial environments.

Looking ahead, positioning will also play an important role in evolutions such as 5G Advanced and, in the longer term, 6G. Fraunhofer IIS is involved in related research, with a focus on positioning and AI-assisted approaches.

Our service offering

As a reliable partner, Fraunhofer IIS supports you in consulting, developing and implementing 5G positioning projects. Drawing on our many years of experience in radio-based positioning and project management, we take your requirements into account and support you from the initial concept through to practical testing and validation. Our technology-agnostic consultancy can also include combinations of different positioning technologies, depending on the application.

Consulting and training

Consulting on the introduction of positioning and 5G cellular technologies
Technology studies (e.g., assessing the suitability of positioning technologies for your specific use case)
Customized training on positioning and 5G cellular technology

Development

Development of solutions in the areas of positioning and 5G mobile communications
Deployment and adaptation of positioning algorithms/software to your systems and requirements
Support with the integration of 5G

Implementation

Problem identification and development of tailored solution concepts
Support in designing campus networks for robust communication and accurate positioning
Ongoing consulting support throughout planning and implementation

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We enable the efficient execution of your R&D projects.

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Applications and projects in 5G positioning

5G positioning is particularly relevant wherever precise real-time location data is required to control and optimize processes. Typical application areas range from industrial and logistics scenarios to use cases in public spaces, as well as healthcare and medical applications and emergency response. At Fraunhofer IIS, such applications are investigated and advanced within research and development projects with a strong focus on real-world deployment. An overview of ongoing and completed 5G positioning projects is compiled on the projects page.

Industry and logistics

Monitoring and control of AMRs / UAVs
Digitalized material flow / warehouse management
Intelligent tool tracking
AR-assisted assembly
Prevention of cargo theft
Industrial Internet of Things (IIoT)

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Smart City

Improved traffic flow
Autonomous driving
Drones for parking logistics
Modern mobility concepts
Digital construction site
Mobile environmental sensing
Connected mobility
Automated vehicle merging

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Smart Health

Asset tracking of medical devices
Breaking chains of infection
Patient protection
Monitoring in medical logistics

Mehr Informationen

Emergency response

Positioning of emergency personnel at the incident site
Drones and autonomous vehicles for improved situational awareness

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Projects

At Fraunhofer IIS, the described applications are implemented and investigated in various research and development projects.

An overview of ongoing and completed projects in the field of 5G positioning.

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Technologies and methods for 5G positioning

5G positioning comprises a range of technical approaches and methods. At Fraunhofer IIS, we investigate both fundamental concepts of 5G positioning and specific methods - for example for industrial applications. The following pages provide an overview of the technological foundations of 5G positioning and illustrate an example of a concrete method.

Technologies and methods for 5G positioning

Overview of 5G positioning technologies and methods at Fraunhofer IIS

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Uplink TDoA: 5G positioning in industrial environments

Overview of uplink-based Time Difference of Arrival (TDoA) and its use in industrial applications.

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Test options for 5G positioning

To test and evaluate 5G positioning, Fraunhofer IIS provides various test environments. They enable investigations under realistic conditions - from measuring and analyzing positioning performance to validating algorithms and AI-assisted approaches in representative scenarios. The test options cover different settings: stationary industrial environments, flexible measurement campaigns at changing locations, and mobile infrastructures for field tests. This allows 5G-based positioning methods to be assessed independently of existing boundary conditions and transferred into concrete applications.

Industry 4.0 5G Positioning and Communication Testbed

Stationary test environment for investigating 5G positioning in industrial scenarios, for example in production, logistics, or warehouse/hall environments.

TO THE “INDUSTRY 4.0” TESTBED

Nomadic 5G positioning testbed

A flexible test environment for temporary measurement campaigns and positioning tests at changing deployment sites and under varying boundary conditions.

TO THE NOMADIC TESTBED

Mobile campus network

Mobile 5G infrastructure for testing positioning methods outside fixed test environments - for example in field trials or multi-site scenarios.

TO THE MOBILE CAMPUS NETWORK

News and events

Press coverage and events document research, demonstrators, and the transfer into real-world practice.

News

Veranstaltungen

Publications

Our research on 5G-based positioning and data-driven methods (machine learning / AI) is published in international journals, conference proceedings, and edited scientific volumes. The following selection provides an overview of key publications from recent years.

2024

Stahlke, M., Feigl, T., Kram, S., Ott, J., Seitz, J., & Mutschler, C. (2024). Data-driven Wireless Positioning. In Unlocking Artificial Intelligence. Springer, Cham.

Ott, J., Pirkl, J., Stahlke, M., Feigl, T., & Mutschler, C. (2024). Radio Foundation Models: Pre-training Transformers for 5G-based Indoor Localization. 14th International Conference on Indoor Positioning and Indoor Navigation (IPIN), Kowloon, Hong Kong, pp. 1–6.

Stahlke, M., Yammine, G., Feigl, T., Eskofier, B. M., & Mutschler, C. (2024). Velocity-Based Channel Charting With Spatial Distribution Map Matching. IEEE Journal of Indoor and Seamless Positioning and Navigation, 2, 230–239.

Ott, J., Stahlke, M., Feigl, T., & Mutschler, C. (2024). Estimating Multipath Component Delays With Transformer Models. IEEE Journal of Indoor and Seamless Positioning and Navigation, 2, 219–229.

2023

Stahlke, M., Yammine, G., Feigl, T., Eskofier, B. M., & Mutschler, C. (2023). Indoor Localization With Robust Global Channel Charting: A Time-Distance-Based Approach. IEEE Transactions on Machine Learning in Communications and Networking, 1, 3–17.

Stahlke, M., Feigl, T., Kram, S., Eskofier, B. M., & Mutschler, C. (2023). Uncertainty-based Fingerprinting Model Selection for Radio Localization. 13th International Conference on Indoor Positioning and Indoor Navigation (IPIN), Nuremberg, Germany, pp. 1–6.

Ott, J., Stahlke, M., Kram, S., Feigl, T., & Mutschler, C. (2023). Multipath Delay Estimation in Complex Environments using Transformer. 13th International Conference on Indoor Positioning and Indoor Navigation (IPIN), Nuremberg, Germany, pp. 1–6.

2022

Stahlke, M., Kram, S., Ott, F., Feigl, T., & Mutschler, C. (2022). Estimating TOA Reliability With Variational Autoencoders. IEEE Sensors Journal, 22(6), 5133–5140.

Stahlke, M., Feigl, T., García, M. H. C., Stirling-Gallacher, R. A., Seitz, J., & Mutschler, C. (2022). Transfer Learning to adapt 5G AI-based Fingerprint Localization across Environments. IEEE 95th Vehicular Technology Conference (VTC2022-Spring), Helsinki, Finland, pp. 1–5.

Kram, S., Kraus, C., Stahlke, M., Feigl, T., Thielecke, J., & Mutschler, C. (2022). Delay Estimation in Dense Multipath Environments using Time Series Segmentation. IEEE Wireless Communications and Networking Conference (WCNC), Austin, TX, USA, pp. 1671–1676.

2021

Feigl, T., Eberlein, E., Kram, S., & Mutschler, C. (2021). Robust ToA-Estimation using Convolutional Neural Networks on Randomized Channel Models. International Conference on Indoor Positioning and Indoor Navigation (IPIN), Lloret de Mar, Spain, pp. 1–8.

Yammine, G., et al. (2021). Experimental Investigation of 5G Positioning Performance Using a mmWave Measurement Setup. International Conference on Indoor Positioning and Indoor Navigation (IPIN), Lloret de Mar, Spain, pp. 1–8.

Altstidl, T., Kram, S., Herrmann, O., Stahlke, M., Feigl, T., & Mutschler, C. (2021). Accuracy-Aware Compression of Channel Impulse Responses using Deep Learning. International Conference on Indoor Positioning and Indoor Navigation (IPIN), Lloret de Mar, Spain, pp. 1–8.

Feigl, T. (2021). Datengetriebene Methoden zur Bestimmung von Position und Orientierung in funk- und trägheitsbasierter Koppelnavigation (Dissertation). FAU – Technische Fakultät.

2020

Stahlke, M., Kram, S., Mutschler, C., & Mahr, T. (2020). NLOS Detection using UWB Channel Impulse Responses and Convolutional Neural Networks. International Conference on Localization and GNSS (ICL-GNSS), Tampere, Finland, pp. 1–6.

2019

Niitsoo, A., Edelhäußer, T., Eberlein, E., Hadaschik, N., & Mutschler, C. (2019). A Deep Learning Approach to Position Estimation from Channel Impulse Responses. Sensors, 19, 1064.

Stahlke, M., Feigl, T., Kram, S., Mumme, T., & Seitz, J. (2019). Discrete Positioning Using UWB Channel Impulse Responses and Machine Learning. International Conference on Localization and GNSS (ICL-GNSS), Nuremberg, Germany, pp. 1–6.

2018

Niitsoo, A., Edelhäußer, T., & Mutschler, C. (2018). Convolutional Neural Networks for Position Estimation in TDoA-Based Locating Systems. International Conference on Indoor Positioning and Indoor Navigation (IPIN), Nantes, France, pp. 1–8.

Feigl, T., Nowak, T., Philippsen, M., Edelhäußer, T., & Mutschler, C. (2018). Recurrent Neural Networks on Drifting Time-of-Flight Measurements. International Conference on Indoor Positioning and Indoor Navigation (IPIN), Nantes, France, pp. 206–212.