A Neural Method for Identifying Transmission Source Locations

Author

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

Author_Institution

Penn State, PA

fYear

2006

fDate

11-14 Sept. 2006

Firstpage

1

Lastpage

5

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

Keywords

Bluetooth; neural nets; transport protocols; wireless LAN; Bluetooth; GPS; IEEE 802.11; RF signal-to-noise ratio; neural method; neural networks; node localization; packet statistics; transmission protocols; transmission source locations; Access protocols; Bluetooth; Communication networks; Global Positioning System; Network servers; Position measurement; Radio frequency; Radiofrequency identification; Signal to noise ratio; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

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

Conference_Location

Helsinki

Print_ISBN

1-4244-0329-4

Electronic_ISBN

1-4244-0330-8

Type

conf

DOI

10.1109/PIMRC.2006.254049

Filename

4022271