Problem
Research questions and friction points this paper is trying to address.
accurate positioning
indoor and dense urban environments
satellite-based systems
standardized 5G localization solutions
commercial devices
RUN-O-RAN: An O-RAN-Native Architecture Enabling Cooperative Uplink Localization
🤖 AI Summary
本文提出RUN-O-RAN框架，利用5G设备的标准SRS信号实现上行定位，解决室内和密集城市环境中精确定位问题。
📝 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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
O-RAN-native
Cooperative SRS
Uplink localization
Network-centric
Non-serving base stations
🔎 Similar Papers
No similar papers found.
