3D Indoor Localization using 5G-based Particle Filtering and CAD Plans

Fifth-generation (5G) technologies will enable new features in the indoor positioning domain. It could be considered as the second big development after the innovation of smartphones. The experimental projects have already been started, and the majority of the people will have access to the 5G positioning services very soon. By standing on the standard methods for the indoor localization like particle filter (PF) and pedestrian dead reckoning (PDR), it is tried to clarify the current challenges based on the actual third generation partnership project (3GPP) specification. In this paper, we have opened a novel interpretation of accuracy and precision understanding specialized for indoor localization by using a space detection. Our designed and developed 5G simulation as well as the 5G-based PF fusion resulted in a reliable localization performance. For this, we have proposed two approaches: (1) map data with the minimum amount of effort out of computer-aided design (CAD) plans and (2) accuracy clarification of the positioning techniques performance followed by a simple 5G-based PF which uses map information and geospatial analyses, smartphone sensor values, and 5G simulation as input to provides a 3D trajectory for a long time robust performance in both online and offline environments. Finally, the target accuracy of a 5G campus network is determined by the numerical results and discussion.