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Fundamental Bounds on Position Estimation Using Proximity Reports
Ericsson Research, Linköping, Sweden.
Ericsson Research, Linköping, Sweden.
Ericsson Research, Linköping, Sweden.
2016 (English)Conference paper, Published paper (Refereed)
Abstract [en]

There is a big trend nowadays toward indoor proximity report based positioning. A binary valued proximity report can be obtained opportunistically through event-triggering, leading to significantly reduced signaling overhead for wireless communications. In this paper, we aim to derive two types of fundamental lower bound, namely the Cram´er-Rao bound and the Barankin bound, on the mean-square-error of any proximity report based position estimator. Using the maximum-likelihood estimator as a representative example, we show that the Barankin bound is potentially much tighter than the Cram´er-Rao bound and conclude that the Barankin bound ought be better suited for benchmarking any proximity report based position estimator.

Place, publisher, year, edition, pages
2016.
Keyword [en]
Barankin bound, Cramér-Rao bound, mean-square-error, position estimation, proximity report.
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-129760OAI: oai:DiVA.org:liu-129760DiVA: diva2:943184
Conference
IEEE 83rd Vehicular Technology Conference: VTC2016-Spring 15–18 May 2016, Nanjing, China
Available from: 2016-06-27 Created: 2016-06-27 Last updated: 2016-07-06Bibliographically approved

Open Access in DiVA

VTC2016BB(367 kB)58 downloads
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Type fulltextMimetype application/pdf

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • vancouver
  • Other style
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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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