Experimental Validation of a 3GPP Compliant 5G-Based Positioning System

TL;DR

This paper presents a 3GPP-compliant 5G positioning testbed, models time offsets affecting TOA estimates, and proposes calibration methods to improve positioning accuracy for applications like public safety and vehicular systems.

Contribution

We develop a 3GPP-compliant 5G positioning testbed, model time offsets, and introduce calibration techniques to enhance positioning performance.

Findings

Mathematical model of time offsets affecting TOA estimates

Calibration method improves positioning accuracy

Experimental validation supports the model and calibration effectiveness

Abstract

The advent of 5G positioning techniques by 3GPP has unlocked possibilities for applications in public safety, vehicular systems, and location-based services. However, these applications demand accurate and reliable positioning performance, which has led to the proposal of newer positioning techniques. To further advance the research on these techniques, in this paper, we develop a 3GPP-compliant 5G positioning testbed, incorporating gNodeBs (gNBs) and User Equipment (UE). The testbed uses New Radio (NR) Positioning Reference Signals (PRS) transmitted by the gNB to generate Time of Arrival (TOA) estimates at the UE. We mathematically model the inter-gNB and UE-gNB time offsets affecting the TOA estimates and examine their impact on positioning performance. Additionally, we propose a calibration method for estimating these time offsets. Furthermore, we investigate the environmental impact on the TOA estimates. Our findings are based on our mathematical model and supported by experimental results.