Fuzzy inference with parameter identification for indoor WLAN positioning

M. Alakhras, M. Oussalah, M. I. Hussein

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


This paper considers the fuzzy inference as position estimator for WLAN indoor environments, based on received signal strength measurements RSS. The proposal algorithm includes a fuzzy inference which uses the k-nearest neighbor classification in signal space, where the position of target node is calculated as a weighted combination of nearest fingerprints, where the weights are estimated using enhanced Takagi-Sugeno fuzzy controller with multivariable inputs and parameter identification with constrained optimization. The new developed technique is proposed to enhance the accuracy of position estimation in WLAN indoor environments.

Original languageEnglish
Title of host publicationWCE 2015 - World Congress on Engineering 2015
EditorsS. I. Ao, Len Gelman, Alexander M. Korsunsky, S. I. Ao, David W.L. Hukins, Andrew Hunter, S. I. Ao, Len Gelman
PublisherNewswood Limited
Number of pages8
ISBN (Electronic)9789881925343
Publication statusPublished - 2015
Event2015 World Congress on Engineering, WCE 2015 - London, United Kingdom
Duration: Jul 1 2015Jul 3 2015

Publication series

NameLecture Notes in Engineering and Computer Science
ISSN (Print)2078-0958


Other2015 World Congress on Engineering, WCE 2015
Country/TerritoryUnited Kingdom


  • Clustering
  • Fuzzy logic
  • RSS
  • WLAN indoor positioning

ASJC Scopus subject areas

  • Computer Science (miscellaneous)


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