5G Positioning and Mapping with Diffuse Multipath

Fuxi Wen; Josef Kulmer; Klaus Witrisal; Henk Wymeersch

doi:10.1109/TWC.2020.3031180

5G Positioning and Mapping with Diffuse Multipath

Fuxi Wen^*, Josef Kulmer, Klaus Witrisal, Henk Wymeersch

^*Korrespondierende/r Autor/-in für diese Arbeit

Institut für Signalverarbeitung und Sprachkommunikation (4420)

Publikation: Beitrag in einer Fachzeitschrift › Artikel › Begutachtung

Abstract

5G mmWave communication is useful for positioning due to the geometric connection between the propagation channel and the propagation environment. Channel estimation methods can exploit the resulting sparsity to estimate parameters (delay and angles) of each propagation path, which in turn can be exploited for positioning and mapping. When paths exhibit significant spread in either angle or delay, these methods break down or lead to significant biases. We present a novel tensor-based method for channel estimation that allows estimation of mmWave channel parameters in a non-parametric form. The method is able to accurately estimate the channel, even in the absence of a specular component. This in turn enables positioning and mapping using only diffuse multipath. Simulation results are provided to demonstrate the efficacy of the proposed approach.

Originalsprache	englisch
Aufsatznummer	9234644
Seiten (von - bis)	1164-1174
Seitenumfang	11
Fachzeitschrift	IEEE Transactions on Wireless Communications
Jahrgang	20
Ausgabenummer	2
DOIs	https://doi.org/10.1109/TWC.2020.3031180
Publikationsstatus	Veröffentlicht - Feb. 2021

ASJC Scopus subject areas

Angewandte Informatik
Elektrotechnik und Elektronik
Angewandte Mathematik

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Boano, C. A. (Teilnehmer (Co-Investigator)), Kubin, G. (Teilnehmer (Co-Investigator)), Bloem, R. (Teilnehmer (Co-Investigator)), Horn, M. (Teilnehmer (Co-Investigator)), Pernkopf, F. (Teilnehmer (Co-Investigator)), Zakany, N. (Teilnehmer (Co-Investigator)), Mangard, S. (Teilnehmer (Co-Investigator)), Witrisal, K. (Teilnehmer (Co-Investigator)), Römer, K. U. (Teilnehmer (Co-Investigator)), Aichernig, B. (Teilnehmer (Co-Investigator)), Bösch, W. (Teilnehmer (Co-Investigator)), Baunach, M. C. (Teilnehmer (Co-Investigator)), Tappler, M. (Teilnehmer (Co-Investigator)), Malenko, M. (Teilnehmer (Co-Investigator)), Weiser, S. (Teilnehmer (Co-Investigator)), Eichlseder, M. (Teilnehmer (Co-Investigator)), Leitinger, E. (Teilnehmer (Co-Investigator)), Grosinger, J. (Teilnehmer (Co-Investigator)), Großwindhager, B. (Teilnehmer (Co-Investigator)), Ebrahimi, M. (Teilnehmer (Co-Investigator)), Alothman Alterkawi, A. B. (Teilnehmer (Co-Investigator)), Knoll, C. (Teilnehmer (Co-Investigator)), Teschl, R. (Teilnehmer (Co-Investigator)), Saukh, O. (Teilnehmer (Co-Investigator)), Rath, M. (Teilnehmer (Co-Investigator)), Steinberger, M. (Teilnehmer (Co-Investigator)), Steinbauer-Wagner, G. (Teilnehmer (Co-Investigator)) & Tranninger, M. (Teilnehmer (Co-Investigator))
1/01/16 → 31/03/22
Projekt: Forschungsprojekt

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title = "5G Positioning and Mapping with Diffuse Multipath",

abstract = "5G mmWave communication is useful for positioning due to the geometric connection between the propagation channel and the propagation environment. Channel estimation methods can exploit the resulting sparsity to estimate parameters (delay and angles) of each propagation path, which in turn can be exploited for positioning and mapping. When paths exhibit significant spread in either angle or delay, these methods break down or lead to significant biases. We present a novel tensor-based method for channel estimation that allows estimation of mmWave channel parameters in a non-parametric form. The method is able to accurately estimate the channel, even in the absence of a specular component. This in turn enables positioning and mapping using only diffuse multipath. Simulation results are provided to demonstrate the efficacy of the proposed approach.",

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author = "Fuxi Wen and Josef Kulmer and Klaus Witrisal and Henk Wymeersch",

note = "Funding Information: Manuscript received December 18, 2019; revised May 9, 2020 and October 7, 2020; accepted October 9, 2020. Date of publication October 21, 2020; date of current version February 11, 2021. This work was supported in part by the Marie Sk{\l}odowska-Curie Grant under Agreement 700044, in part by the Swedish Research Council under Grant 2018-03701, and in part by the Graz University of Technology under the Lead Project “Dependable Things”. The associate editor coordinating the review of this article and approving it for publication was P. Casari. (Corresponding author: Fuxi Wen.) Fuxi Wen is with the School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China (e-mail: [email protected]). Publisher Copyright: {\textcopyright} 2002-2012 IEEE.",

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N2 - 5G mmWave communication is useful for positioning due to the geometric connection between the propagation channel and the propagation environment. Channel estimation methods can exploit the resulting sparsity to estimate parameters (delay and angles) of each propagation path, which in turn can be exploited for positioning and mapping. When paths exhibit significant spread in either angle or delay, these methods break down or lead to significant biases. We present a novel tensor-based method for channel estimation that allows estimation of mmWave channel parameters in a non-parametric form. The method is able to accurately estimate the channel, even in the absence of a specular component. This in turn enables positioning and mapping using only diffuse multipath. Simulation results are provided to demonstrate the efficacy of the proposed approach.

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5G Positioning and Mapping with Diffuse Multipath

Abstract

ASJC Scopus subject areas

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