GDOP Based BS Selection for Positioning in mmWave 5G NR Networks

TL;DR

This paper proposes a GDOP-based base station selection algorithm for mmWave 5G NR networks that improves user positioning accuracy by optimizing the geometric distribution of BSs, reducing resource use.

Contribution

It introduces a novel BS selection method based on GDOP for enhanced positioning accuracy in mmWave 5G systems with mixed LOS/NLOS environments.

Findings

Higher positioning accuracy achieved with fewer radio resources.

Effective in indoor and outdoor scenarios with beam-based mmWave communication.

GDOP-based selection outperforms other methods in simulations.

Abstract

The fifth-generation (5G) of mobile communication supported by millimetre-wave (mmWave) technology and higher base station (BS) densification facilitate to enhance user equipment (UE) positioning. Therefore, 5G cellular system is designed with many positioning measurements and special positioning reference signals with a multitude of configurations for a variety of use cases, expecting stringent positioning accuracies. One of the major factors that the accuracy of a particular position estimate depends on is the geometry of the nodes in the system, which could be measured with the geometric dilution of precision (GDOP). Hence in this paper, we investigate the time difference of arrival (TDOA) measurements based UE positioning accuracy improvement, exploiting the geometric distribution of BSs in mixed LOS and NLOS environment. We propose a BS selection algorithm for UE positioning based on the GDOP of the BSs participating in the positioning process. Simulations are conducted for indoor and outdoor scenarios that use antenna arrays with beam-based mmWave NR communication. Results demonstrate that the proposed BS selection can achieve higher positioning accuracy with fewer radio resources compared to the other BS selection methods.