Theoretical entropy assessment of fingerprint-based Wi-Fi localization accuracy

  • Authors:

  • Mu Zhou;Zengshan Tian;Kunjie Xu;Xiang Yu;Haibo Wu

  • Affiliations:

  • Chongqing Key Lab of Mobile Communications Technology, Chongqing University of Posts and Telecommunications, Chongqing, China;Chongqing Key Lab of Mobile Communications Technology, Chongqing University of Posts and Telecommunications, Chongqing, China;Graduate Telecommunications and Networking Program, University of Pittsburgh, PA, USA;Chongqing Key Lab of Mobile Communications Technology, Chongqing University of Posts and Telecommunications, Chongqing, China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2013

Quantified Score

Hi-index 12.05

Visualization

Abstract

The fingerprint-based Wi-Fi localization technology has been recognized as one of the remarkable solutions to the future ubiquitous location based services (LBSs) in indoor and underground environment. Thus, how to evaluate the performance of fingerprint-based localization has attracted significant attentions. In this paper, we propose localization entropy as a novel metric to effectively and efficiently evaluate the accuracy of fingerprint-based Wi-Fi localization. Based on a simple NxM centrosymmetric model with the logarithmic Gaussian distribution, the relations among the localization precision, entropy and expected errors in the cases of none, one, two and three hearable access points (APs) have been carefully discussed. Furthermore, we conduct a series of simulations and experiments to examine the reliability and time-efficiency of our proposed performance metric (i.e., localization entropy) in a variety of reference point (RP) densities and received signal strength (RSS) standard deviations.