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New neural network based mobile location estimation in urban propagation models

  • J. Muhammad*
  • , A. Hussain
  • , W. M. Ahmed
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings - INMIC 2003
Subtitle of host publicationIEEE 7th International Multi Topic Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages146-150
Number of pages5
ISBN (Electronic)0780381831, 9780780381834
DOIs
StatePublished - 2003
Externally publishedYes

Publication series

NameProceedings - INMIC 2003: IEEE 7th International Multi Topic Conference

Bibliographical note

Publisher Copyright:
© 2003 IEEE.

Keywords

  • Cellular networks
  • Central office
  • Communication switching
  • Global Positioning System
  • Intelligent networks
  • Land mobile radio cellular systems
  • Mathematical model
  • Neural networks
  • Telephone sets
  • Telephony

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Signal Processing
  • Modeling and Simulation

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