By Topic

Neural network and fingerprinting-based geolocation on time-varying channels

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Nerguizian, C. ; Ecole Polytech. de Montreal, Que. ; Despins, C. ; Affes, S. ; Wassi, G.I.
more authors

In a harsh indoor environment, fingerprinting geolocation techniques perform better than the traditional ones, based on triangulation, because multipath is used as constructive information. However, this is generally true in static environments as fingerprinting techniques suffer degradations in location accuracy in dynamic environments where the properties of the channel change in time. This is due to the fact that the technique needs a new database collection when a change of the channel's state occurs. In this paper, a novel solution based on a hierarchy of artificial neural networks (ANNs) is proposed to enhance such a geolocation system. It is shown that the enhanced system detects the change in the channel's properties via geolocation reference points, identifies the new channel state and activates a new database that best represents the current radio environment

Published in:

Personal, Indoor and Mobile Radio Communications, 2006 IEEE 17th International Symposium on

Date of Conference:

11-14 Sept. 2006