By Topic

Indoor cell-level localization based on RSSI classification

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
$33 $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

2 Author(s)
Kung-Chung Lee ; Dept. of Electr. & Comput. Eng., Univ. of British Columbia, Vancouver, BC, Canada ; Lutz Lampe

The task of estimating the location of a mobile transceiver using the Received Signal Strength Indication (RSSI) values of radio transmissions is an inference problem. Contextual information, i.e., if the target is in a specific region, is sufficient for most applications. Therefore, instead of estimating position coordinates, we take a slightly different approach and look at localization as a classification problem. We perform a comparison between the K-Nearest Neighbor (KNN), the Support Vector Machine (SVM) and the Simple Gaussian Classifier (SGC), three classifiers proposed previously under different contexts. Using experimental results, we demonstrate that the SGC achieves a competitive performance despite its simplicity. Furthermore, we consider the extension of the SGC to a Hidden Markov Model (HMM) and demonstrate the performance gains. The derivative of the HMM filter allows us to do online parameter tracking, realizing an adaptive scheme. To our knowledge, this adaptive scheme has not been used for the SGC before. Considering the advantages of the SGC, we advocate the SGC as a competitive solution for estimating contextual location information.

Published in:

Electrical and Computer Engineering (CCECE), 2011 24th Canadian Conference on

Date of Conference:

8-11 May 2011