A neural method for identifying transmission source locations

Thomas L. Hemminger, David R. Loker, Carlos Pomalaza-Raez

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

1 Scopus citations

Abstract

In recent years, there has been great interest in node localization within low-power communication networks. These technologies include Bluetooth, GPS, IEEE 802.11, and other transmission protocols. Most techniques are based on variations in the RF signal-to-noise ratio, but this paper introduces a new method, which employs packet statistics. In this work, packet information was collected from several stationary clients while moving a portable server and access point. Packet statistics and the corresponding server locations were subsequently used to train neural networks. Our studies have shown that the networks can determine the location of additional transmitters based on the packet histories of the stationary clients.

Original languageEnglish (US)
Title of host publication2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
DOIs
StatePublished - Dec 1 2006
Event2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC - Helsinki, Finland
Duration: Sep 11 2006Sep 14 2006

Publication series

NameIEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC

Other

Other2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
CountryFinland
CityHelsinki
Period9/11/069/14/06

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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