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Direct Localization for Massive MIMO
Chalmers, Sweden.
Chalmers, Sweden.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-7599-4367
New Jersey Institute Technology, NJ 07102 USA.
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2017 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 65, no 10, 2475-2487 p.Article in journal (Refereed) Published
Abstract [en]

Large-scale MIMO systems are well known for their advantages in communications, but they also have the potential for providing very accurate localization, thanks to their high angular resolution. A difficult problem arising indoors and outdoors is localizing users over multipath channels. Localization based on angle of arrival (AOA) generally involves a two-step procedure, where signals are first processed to obtain a users AOA at different base stations, followed by triangulation to determine the users position. In the presence of multipath, the performance of these methods is greatly degraded due to the inability to correctly detect and/or estimate the AOA of the line-of-sight (LOS) paths. To counter the limitations of this two-step procedure which is inherently suboptimal, we propose a direct localization approach in which the position of a user is localized by jointly processing the observations obtained at distributed massive MIMO base stations. Our approach is based on a novel compressed sensing framework that exploits channel properties to distinguish LOS from non-LOS signal paths, and leads to improved performance results compared to previous existing methods.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2017. Vol. 65, no 10, 2475-2487 p.
Keyword [en]
MIMO; multipath channels; position measurement; 5G mobile communication; direction-of-arrival estimation; navigation; antenna arrays; signal processing algorithms; compressed sensing; sparse matrices; parameter estimation; base stations
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:liu:diva-137078DOI: 10.1109/TSP.2017.2666779ISI: 000398670800001OAI: oai:DiVA.org:liu-137078DiVA: diva2:1093287
Note

Funding Agencies|European Research Council [258418]; EU HIGHTS project (High precision positioning for cooperative ITS applications) [MG-3.5a-2014-636537]

Available from: 2017-05-05 Created: 2017-05-05 Last updated: 2017-05-05

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CiteExportLink to record
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Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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