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Online prediction of spatial fields for radio-frequency communication
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
Ericsson Res, Kista, Sweden.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
2016 (English)In: Proc. 24th European Signal Processing Conference, Piscataway, NJ: IEEE, 2016, p. 1252-1256Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we predict spatial wireless channel characteristics using a stochastic model that takes into account both distance dependent pathloss and random spatial variation due to fading. This information is valuable for resource allocation, interference management, design in wireless communication systems. The spatial field model is trained using a convex covariance-based learning method which can be implemented online. The resulting joint learning and prediction method is suitable for large-scale or streaming data. The online method is first demonstrated on a synthetic dataset which models pathloss and medium-scale fading. We compare the method with a state-of-the-art scalable batch method. It is subsequently tested in a real dataset to capture small-scale variations.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE, 2016. p. 1252-1256
Series
European Signal Processing Conference, ISSN 2076-1465
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:uu:diva-315572DOI: 10.1109/EUSIPCO.2016.7760449ISI: 000391891900239ISBN: 9780992862657 (electronic)OAI: oai:DiVA.org:uu-315572DiVA, id: diva2:1074653
Conference
EUSIPCO 2016, August 29 – September 2, Budapest, Hungary
Available from: 2016-12-01 Created: 2017-02-15 Last updated: 2017-02-27Bibliographically approved

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Zachariah, DaveStoica, Peter

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association
  • 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
  • text
  • asciidoc
  • rtf