Research on LTE Positoning Algorithm under Multipath Environment

Dan, Zesheng; Lian, Baowang; Xu, Hao

doi:10.1109/icspcc.2018.8567820

Cited by 3 publications

(1 citation statement)

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“…The positioning performance was assessed in a simulation scenario considering the EPA and ETU channel models. Simulation results showed that 90% of the position errors provided by the proposed scheme were less than 7 m. The estimation of signal parameters by the rotational invariance technique (ESPRIT) was used in Dan et al (2018) for joint TOA and direction of arrival (DOA) estimation with the CRS considering a UE equipped with two antennas. The positioning performance was only evaluated for static multipath channels.…”

Section: Computer Simulationsmentioning

confidence: 99%

Performance comparison of time‐of‐arrival estimation techniques for LTE signals in realistic multipath propagation channels

Wang

Morton

2020

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Long term evolution (LTE) signals have the potential for use in positioning, especially in challenging environments. The time-of-arrival (TOA)-based technique supported by LTE is attractive due to its high positioning accuracy. However, it is vulnerable to multipath propagation effects in typical LTE channels. This paper will summarize several existing advanced TOA estimators for LTE signals, i.e., first peak detection, information theoretic criteria, super-resolution algorithm, and delay-lock loop (DLL). Later, the paper will evaluate the TOA estimation performances of these techniques with multipath propagation effects and varying signal conditions using simulations. For the DLL, the multipath error envelope metric is assessed for different signal bandwidths. The root mean square errors of the TOA estimations are compared to evaluate suitable TOA estimators under various conditions. Finally, some other performance characteristics of these techniques are also discussed. K E Y W O R D S long term evolution, multipath propagation channel, time-of-arrival estimation This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Computer Simulationsmentioning

confidence: 99%