O-ran architecture enables accurate 5g uplink positioning indoors
RUN-O-RAN: An O-RAN-Native Architecture Enabling Cooperative Uplink Localization
Networking and Internet Architecture
Summary
Finding precise locations indoors or in crowded cities can be tricky because satellite signals often don't reach well there. The authors designed a system called RUN-O-RAN that uses signals inside 5G networks to figure out device locations without changing the devices themselves. It works by letting the cell towers cooperate and measure signal details to calculate positions accurately to within a few meters. Their tests showed this method works well even in challenging conditions and helps improve indoor location services.
What this means in practice
- •For mobile network operators: Enable indoor 5G device positioning using existing uplink signals without hardware changes to user devices.$Commercial implications: Helps operators offer indoor location-based services and diagnostics by leveraging their existing network infrastructure and 5G devices.
- •For emergency response teams: Locate 5G-enabled devices indoors during emergencies without relying on satellite GPS signals.
Authors
Viola Bernazzoli, Alberto Ceresoli, Ilario Filippini
Abstract
Accurate positioning is increasingly required in indoor and dense urban environments; nonetheless, satellite-based systems are not always available, and standardized 5G localization solutions remain difficult to deploy with commercial devices. This paper presents RUN-O-RAN, an O-RAN-native framework that enables network-centric uplink localization using standard Sounding Reference Signal (SRS) transmissions from commercial 5G devices. RUN-O-RAN xApp coordinates serving and neighboring base stations, enabling non-serving base stations to retrieve SRS-based uplink timing measurements that would be unavailable in conventional RAN deployments, without modifying the UE or existing 3GPP signaling procedures. The framework combines cooperative SRS collection, first-path time-of-arrival estimation, timing-advance tracking, clock-drift compensation, and multi-anchor position estimation into a complete network-side localization service. Experimental evaluation over $150,000$ SRS transmissions validates the proposed framework, achieving meter-level localization under diverse propagation conditions while revealing the impact of anchor geometry and multipath on positioning accuracy. These findings demonstrate that cooperative SRS-based localization can be realized within the O-RAN ecosystem without modifying commercial UEs, providing a practical foundation for future network-native ISAC positioning services.