3GPP-assisted high-accuracy GNSS for mass-market services
28.10.2026
08:00 - 09:00 GMT (London)
09:00 - 10:00 CET (Berlin)
17:00 - 18:00 JST (Tokyo)
While 3GPP is best known as the global standard for cellular connectivity, its scope extends beyond that, encompassing services such as positioning and network APIs. This Masterclass, presented jointly by Quectel and Ericsson, introduces 3GPP-assisted high-accuracy GNSS. It covers what it supports, how it is delivered, and what it means for IoT developers building mass-market location-based services.
On its own, GNSS positioning is typically accurate to within 3 to 20 meters, limited by satellite signal errors such as multipath, atmospheric delay, and restricted sky visibility. Centimeter-level accuracy requires additional correction data, delivered to the device from corrections services, based on data from a network of reference stations. 3GPP-assisted GNSS supports several types of assistance data: OSR/network RTK, SSR/PPP-RTK, and integrity data for safety critical applications. Support for these was completed in 2019, 2020, and 2022 respectively, for 4G and 5G, and will continue into 6G.
The session explains why this matters for mass-market IoT. Provisioning happens on the network side rather than the device side. A device can therefore be deployed with any operator, then find and use the service automatically, without any manual setup. Assistance data can be delivered via unicast or cellular broadcast, and device reporting is configurable and consent-based. Costs scale with area covered, not device count, so the approach remains viable at IoT scale. Ericsson has supported unicast delivery for around two years, and recently announced broadcast support after successful e2e tests. An open-source device client stack is also available, to help developers get started quickly.
Service authorization is handled at the network level too, and is separated from the data provider itself. Therefore, multiple providers can supply different types of assistance data across different parts of the network. Together, this is what makes 3GPP-assisted GNSS a standardized, scalable route to high-accuracy positioning for mass-market IoT.
Speakers
Per-Gunnar Andersson
Per-Gunnar Anderson has more than 20 years of experience in the telecom and location industry. He joined Ericsson in 1997 and has been in different roles, including leading product and solution management, regional sales engagement management in the Middle East and Africa, and account sales management in the Nordics. Per-Gunnar holds an MSc in total quality management from Sheffield Hallam University in the UK and a BSc in mechanical engineering from Halmstad University in Sweden.
Job title:
Strategic Product and Business Development Manager
Company:
Ericsson
Fredrik Gunnarsson
Fredrik Gunnarsson joined Ericsson Research in 2001 and has been working on concepts, standardization, prototypes, and knowledge transfer to products for 3rd, 4th, 5th, and now 6th generation cellular communication standards. He was responsible as 3GPP delegate when support for assisted high accuracy GNSS was introduced. He received MSc and PhD degrees in electrical engineering from Linköping University, Sweden in 1996 and 2000, respectively.
Job title:
Positioning Expert
Company:
Ericsson Research
Chang Xu
Chang has extensive GNSS engineering experience. Over the past 10 years, he has worked on a wide range of GNSS applications, including industrial-grade GNSS deformation monitoring, consumer-grade GNSS chip design and implementation, and professional-grade, high-accuracy RTK/PPP-RTK positioning algorithm development.
Job title:
GNSS Product Manager EMEA
Company:
Quectel
Agenda
Why standalone GNSS is not accurate enough
How RTK and PPP-RTK enable centimeter-level positioning
Current correction delivery using NTRIP
Device requirements and mass-market deployment challenges
Quectel high-precision GNSS platforms and applications
What 3GPP LPP changes and what remains the same
OSR, SSR and integrity assistance
Network-based provisioning and authorization
Unicast vs. cellular broadcast
Assistance delivery and consent-based device reporting
The open-source device client stack
Network, device-client and GNSS-platform integration
OSR and SSR test setup
Positioning results and key findings
Considerations for commercial deployment