Integrating 3GPP and Non-3GPP Technologies for Hybrid Positioning in B5G Networks

Positioning is crucial for Beyond 5G (B5G) networks, enabling applications like industrial automation, autonomous transportation, and augmented reality. Despite 3GPP's progress, seamless integration with non-3GPP technologies for indoor localization remains challenging. This work introduces a hybrid fingerprinting method that combines signal strength from both 3GPP and non-3GPP networks, utilizing a private 5G testbed with integrated Wi-Fi access points. The positioning algorithm operates as an xApp within the near-RT RAN Intelligent Controller (RIC). We also propose a novel scheme to link non-3GPP networks with the RIC, enhancing real-time decision-making and improving localization accuracy. Experimental results confirm the effectiveness of our approach.