5GNR Indoor Positioning By Joint DL-TDoA and DL-AoD

Mohsen Ahadi, F. Kaltenberger
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Abstract

Positioning a user terminal based on cellular signals is an attractive solution in situations where accurate positioning based on global navigation satellite systems (GNSS) is not possible, such as inside buildings. The 5G New Radio (NR) networks based on 3GPP have introduced several enhanced features to allow the accurate positioning of user terminals. Especially Frequency Range 2 (FR2) mmWave setups are attractive for localization because the large bandwidths allow for high-resolution estimation of the Time Difference of Arrival (TDoA) while the beamforming capabilities can be exploited to estimate the Angle of Arrival (AoA) or Angle of Departure (AoD) of the signals.In this work, we propose a new UE-based positioning algorithm that combines the Downlink Time Difference of Arrival (DL-TDoA) and Downlink Angle of Departure (DL-AoD) information estimated from the downlink positioning reference signals (DL-PRS) introduced in 3GPP Rel-16. TDoA is a widely used horizontal positioning technique that does not require tight synchronization between base stations and mobile stations. Moreover, multiple antennas beamforming on base stations leads to high vertical positioning accuracy with AoD. We use ray-tracing-based site-specific channel models to evaluate our joint positioning algorithm’s performance in an Indoor Factory (InF) scenario. The simulation results show sub-meter user localization error which is a significant improvement compared to applying the previous methods separately.
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利用DL-TDoA和DL-AoD联合进行5GNR室内定位
在无法使用全球卫星导航系统(GNSS)进行精确定位的情况下,例如在建筑物内,基于蜂窝信号对用户终端进行定位是一种有吸引力的解决方案。基于3GPP的5G新无线电(NR)网络引入了几个增强功能,可以对用户终端进行准确定位。特别是频率范围2 (FR2)毫米波设置对定位很有吸引力,因为大带宽允许高分辨率估计到达时差(TDoA),而波束形成能力可以用来估计信号的到达角(AoA)或出发角(AoD)。在这项工作中,我们提出了一种新的基于ue的定位算法,该算法结合了3GPP Rel-16中引入的下行定位参考信号(DL-PRS)估计的下行到达时差(DL-TDoA)和下行出发角(DL-AoD)信息。TDoA是一种广泛使用的水平定位技术,它不需要基站和移动台之间的紧密同步。此外,基站上的多天线波束形成使得AoD的垂直定位精度很高。我们使用基于光线跟踪的特定站点通道模型来评估我们的联合定位算法在室内工厂(InF)场景中的性能。仿真结果表明,与单独应用上述方法相比,该方法的用户定位误差有了显著提高。
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