ORAN-Sense: Localizing Non-cooperative Transmitters with Spectrum Sensing and 5G O-RAN

Abstract

Crowdsensing networks for the sole purpose of performing spectrum measurements have resulted in prior initiatives that have failed primarily due to their costs for maintenance. In this paper, we take a different view and propose ORAN-Sense, a novel architecture of Internet of Things (IoT) spectrum crowdsensing devices integrated into the Next Generation of cellular networks. We use this framework to extend the capabilities of 5G networks and localize a transmitter that does not collaborate in the process of positioning. While 5G signals can not be applied to this scenario as the transmitter does not participate in the localization process through dedicated pilot symbols and data, we show how to use Time Difference of Arrival-based positioning using low-cost spectrum sensors, minimizing hardware impairments of low-cost spectrum receivers, introducing methods to address errors caused by over-the-air signal propagation, and proposing a low-cost synchronization technique. We have deployed our localization network in two major cities in Europe. Our experimental results indicate that signal localization of noncollaborative transmitters is feasible even using low-cost radio receivers with median accuracies of tens of meters with just a few sensors spanning cities, which makes it suitable for its integration in the Next Generation of cellular networks.