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Optimal KNN positioning algorithm via theoretical accuracy criterion in WLAN indoor environment

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Abstract

This paper proposes the optimal K nearest neighbors (KNN) positioning algorithm via theoretical accuracy criterion (TAC) in wireless LAN (WLAN) indoor environment. As far as we know, although the KNN algorithm is widely utilized as one of the typical distance dependent positioning algorithms, the optimal selection of neighboring reference points (RPs) involved in KNN has not been significantly analyzed. Therefore, in order to fill this gap, the optimal KNN positioning algorithm based on the best TAC is introduced. And this algorithm is beneficial to construct the reliable WLAN indoor positioning system and provide the efficient location based services (LBSs). The relationship among theoretical expectation accuracy, unit interval of neighboring RPs and dimensions of target location region is also revealed. Furthermore, the feasibility and effectiveness of optimal KNN positioning algorithm are verified based on the experimental comparisons respectively in the regular office room, straight corridors, static positioning and dynamic tracking situations.

Original languageEnglish
Title of host publication2010 IEEE Global Telecommunications Conference, GLOBECOM 2010
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781424456383
DOIs
StatePublished - 2010
Event53rd IEEE Global Communications Conference, GLOBECOM 2010 - Miami, United States
Duration: 6 Dec 201010 Dec 2010

Publication series

NameGLOBECOM - IEEE Global Telecommunications Conference

Conference

Conference53rd IEEE Global Communications Conference, GLOBECOM 2010
Country/TerritoryUnited States
CityMiami
Period6/12/1010/12/10

Keywords

  • Accuracy criterion
  • Expectation error
  • Positioning algorithm
  • Radio fingerprint
  • WLAN

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