New neural network based mobile location estimation in urban propagation models

Location estimation finds its applications in many important decisions in cellular networks. Hand offs, cellular fraud detection and location sensitive billing are some of the examples. Many different techniques are currently in use. This work first gives an overview of conventional location estimat...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Muhammad, J., Hussain, A., Ahmed, W.M.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 150
container_issue
container_start_page 146
container_title
container_volume
creator Muhammad, J.
Hussain, A.
Ahmed, W.M.
description Location estimation finds its applications in many important decisions in cellular networks. Hand offs, cellular fraud detection and location sensitive billing are some of the examples. Many different techniques are currently in use. This work first gives an overview of conventional location estimation techniques and applications, and a new signal-strength based neural network technique is then presented. A mobile architecture based on a simulated urban environment is used to assess the generalization performance of the feed forward multi-layered perceptron (MLP) neural network.
doi_str_mv 10.1109/INMIC.2003.1416679
format Conference Proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_1416679</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>1416679</ieee_id><sourcerecordid>1416679</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-1ba046a1bb662c0e44654ec769461f52fdc307a1b129baa1c1d842b519e1abda3</originalsourceid><addsrcrecordid>eNotT81qwzAYM4zBtq4vsF38Asn8xY4TH0fYT6BrL72Xz8mX4S2Jg51S9vYLpLpISCAkxp5ApADCvNT7r7pKMyFkCgq0LswNexBFKWQJpYQ7to3xRyyQJs8Lfc8Oe7rwkc4B-4Xmiw-_3GKklg_eup547xucnR85xdkNq3QjPweLI5-Cn_B7NQffUh8f2W2HfaTtlTfs-P52rD6T3eGjrl53iTNiTsCiUBrBWq2zRpBSOlfUFNooDV2edW0jRbHkkBmLCA20pcpsDoYAbYtyw57XWkdEpyksy8Lf6XpZ_gNoG04L</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>New neural network based mobile location estimation in urban propagation models</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Muhammad, J. ; Hussain, A. ; Ahmed, W.M.</creator><creatorcontrib>Muhammad, J. ; Hussain, A. ; Ahmed, W.M.</creatorcontrib><description>Location estimation finds its applications in many important decisions in cellular networks. Hand offs, cellular fraud detection and location sensitive billing are some of the examples. Many different techniques are currently in use. This work first gives an overview of conventional location estimation techniques and applications, and a new signal-strength based neural network technique is then presented. A mobile architecture based on a simulated urban environment is used to assess the generalization performance of the feed forward multi-layered perceptron (MLP) neural network.</description><identifier>ISBN: 0780381831</identifier><identifier>ISBN: 9780780381834</identifier><identifier>DOI: 10.1109/INMIC.2003.1416679</identifier><language>eng</language><publisher>IEEE</publisher><subject>Cellular networks ; Central office ; Communication switching ; Global Positioning System ; Intelligent networks ; Land mobile radio cellular systems ; Mathematical model ; Neural networks ; Telephone sets ; Telephony</subject><ispartof>7th International Multi Topic Conference, 2003. INMIC 2003, 2003, p.146-150</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1416679$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,777,781,786,787,2052,4036,4037,27906,54901</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1416679$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Muhammad, J.</creatorcontrib><creatorcontrib>Hussain, A.</creatorcontrib><creatorcontrib>Ahmed, W.M.</creatorcontrib><title>New neural network based mobile location estimation in urban propagation models</title><title>7th International Multi Topic Conference, 2003. INMIC 2003</title><addtitle>INMIC</addtitle><description>Location estimation finds its applications in many important decisions in cellular networks. Hand offs, cellular fraud detection and location sensitive billing are some of the examples. Many different techniques are currently in use. This work first gives an overview of conventional location estimation techniques and applications, and a new signal-strength based neural network technique is then presented. A mobile architecture based on a simulated urban environment is used to assess the generalization performance of the feed forward multi-layered perceptron (MLP) neural network.</description><subject>Cellular networks</subject><subject>Central office</subject><subject>Communication switching</subject><subject>Global Positioning System</subject><subject>Intelligent networks</subject><subject>Land mobile radio cellular systems</subject><subject>Mathematical model</subject><subject>Neural networks</subject><subject>Telephone sets</subject><subject>Telephony</subject><isbn>0780381831</isbn><isbn>9780780381834</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2003</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotT81qwzAYM4zBtq4vsF38Asn8xY4TH0fYT6BrL72Xz8mX4S2Jg51S9vYLpLpISCAkxp5ApADCvNT7r7pKMyFkCgq0LswNexBFKWQJpYQ7to3xRyyQJs8Lfc8Oe7rwkc4B-4Xmiw-_3GKklg_eup547xucnR85xdkNq3QjPweLI5-Cn_B7NQffUh8f2W2HfaTtlTfs-P52rD6T3eGjrl53iTNiTsCiUBrBWq2zRpBSOlfUFNooDV2edW0jRbHkkBmLCA20pcpsDoYAbYtyw57XWkdEpyksy8Lf6XpZ_gNoG04L</recordid><startdate>2003</startdate><enddate>2003</enddate><creator>Muhammad, J.</creator><creator>Hussain, A.</creator><creator>Ahmed, W.M.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2003</creationdate><title>New neural network based mobile location estimation in urban propagation models</title><author>Muhammad, J. ; Hussain, A. ; Ahmed, W.M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-1ba046a1bb662c0e44654ec769461f52fdc307a1b129baa1c1d842b519e1abda3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Cellular networks</topic><topic>Central office</topic><topic>Communication switching</topic><topic>Global Positioning System</topic><topic>Intelligent networks</topic><topic>Land mobile radio cellular systems</topic><topic>Mathematical model</topic><topic>Neural networks</topic><topic>Telephone sets</topic><topic>Telephony</topic><toplevel>online_resources</toplevel><creatorcontrib>Muhammad, J.</creatorcontrib><creatorcontrib>Hussain, A.</creatorcontrib><creatorcontrib>Ahmed, W.M.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Muhammad, J.</au><au>Hussain, A.</au><au>Ahmed, W.M.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>New neural network based mobile location estimation in urban propagation models</atitle><btitle>7th International Multi Topic Conference, 2003. INMIC 2003</btitle><stitle>INMIC</stitle><date>2003</date><risdate>2003</risdate><spage>146</spage><epage>150</epage><pages>146-150</pages><isbn>0780381831</isbn><isbn>9780780381834</isbn><abstract>Location estimation finds its applications in many important decisions in cellular networks. Hand offs, cellular fraud detection and location sensitive billing are some of the examples. Many different techniques are currently in use. This work first gives an overview of conventional location estimation techniques and applications, and a new signal-strength based neural network technique is then presented. A mobile architecture based on a simulated urban environment is used to assess the generalization performance of the feed forward multi-layered perceptron (MLP) neural network.</abstract><pub>IEEE</pub><doi>10.1109/INMIC.2003.1416679</doi><tpages>5</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISBN: 0780381831
ispartof 7th International Multi Topic Conference, 2003. INMIC 2003, 2003, p.146-150
issn
language eng
recordid cdi_ieee_primary_1416679
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Cellular networks
Central office
Communication switching
Global Positioning System
Intelligent networks
Land mobile radio cellular systems
Mathematical model
Neural networks
Telephone sets
Telephony
title New neural network based mobile location estimation in urban propagation models
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-18T14%3A26%3A01IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=New%20neural%20network%20based%20mobile%20location%20estimation%20in%20urban%20propagation%20models&rft.btitle=7th%20International%20Multi%20Topic%20Conference,%202003.%20INMIC%202003&rft.au=Muhammad,%20J.&rft.date=2003&rft.spage=146&rft.epage=150&rft.pages=146-150&rft.isbn=0780381831&rft.isbn_list=9780780381834&rft_id=info:doi/10.1109/INMIC.2003.1416679&rft_dat=%3Cieee_6IE%3E1416679%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=1416679&rfr_iscdi=true