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There have been many research efforts in the area of localization in recentyears. Especially within the Internet of Things (IoT), the knowledge ofposition information for individual components is of great interest, forexample, in asset tracking, to name just one. However, many of these use casesrequire a high energy efficiency, making a GNSS-based approach infeasible. Onepromising candidate can be found in Low Power Wide Area Networks (LPWAN), whichenable battery lifetimes of up to 20 years. However, no gold standard forlocalization exists for these types of networks. Our work proposes a testbedarchitecture that allows the investigation and development of localizationalgorithms within LPWA Networks. The concept is built on a Cloud Radio AccessNetwork (CRAN) architecture that allows the streaming of IQ from remote basestations to a central processing unit. Furthermore, the architecture isexpanded by a synchronization concept based on Signals of Opportunity (SoO) toenable the testbed for runtime-based positioning. Therefore, we propose ahardware concept consisting of antennas and a low-cost off-the-shelfsoftware-defined radio (SDR)-based frontend architecture and a softwareframework using a hypertext transfer protocol (HTTP)-based server and clientarchitecture. The proposed system is installed in an urban environment. Initialmeasurements are conducted, where it can be shown that the proposedarchitecture can be used for highly precise Time Difference of Arrival (TDoA)measurements, offering the possibility of time synchronization down toapproximately 200 ps and frequency synchronization of 3 mHz.

IoT Cloud RAN Testbed for Ultra-Precise TDoA-based Localization in LPWANs