Beam-based vehicular position estimation in 5G radio access

• Published in: 2018 IEEE Wireless Communications and Networking Conference (WCNC) pp. 1 - 6
• Main Authors: Zhang, Xin, Razavi, Sara Modarres, Gunnarsson, Fredrik, Larsson, Kjell, Manssour, Jawad, Na, Minsoo, Choi, Changsoon, Jo, Sungho
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.04.2018
• Subjects: 5G mobile communication; Antennas; Conferences; Estimation; Long Term Evolution; Multiple signal classification; Uplink
• ISSN: 1558-2612
• DOI: 10.1109/WCNC.2018.8377434

Positioning is recognized as an important feature in cellular networks due to regulatory requirements on emergency calls, but also to its potential for massive commercial applications, such as intelligent transportation, entertainment, industry automation, robotics, remote operation, healthcare, smart parking, etc. The standardization of the fifth generation (5G) has started, and one fundamental feature is beamforming, where it is possible to support both connected and idle mode users via fixed or flexible beams. 5G positioning is yet to be defined, and in this paper we show positioning results based on data from beam tracking and uplink timing alignment in a 5G radio access testbed. This specific testbed is operating at a carrier frequency of 28 GHz and is deployed with multiple transmission points at a race track to show 5G performance at different vehicular speeds. In this paper, positioning is based on estimated angle of arrival (AoA) using the MUltiple SIgnal Classification (MUSIC) algorithm and estimated range using the uplink time alignment procedure. The position estimation is evaluated with Global Positioning System (GPS) data as reference. The evaluation studies show that horizontal position error at 70 percentile is 1 meter for 10 km/h tested speed and 3 meters for 120 km/h tested speed.