Mobile station location estimation using an artificial neural network (ANN)
Other Title(s)
تقدير موقع المحطة النقالة باستخدام الشبكات العصبية الذكية
Dissertant
Abd al-Hadi, Qusayy Abd al-Khaliq
Thesis advisor
Comitee Members
Marhun, Ali F.
Abd al-Hasan, Abbas M.
Ali, Hamid A.
Abd Allah, Abd al-Karim Y.
University
University of Basrah
Faculty
Science College
Department
Department of Computer Science
University Country
Iraq
Degree
Master
Degree Date
2013
English Abstract
Today, there is great interest in developing location-based services in wireless communication due to its many applications in the different life fields.
This thesis presents a mobile station location estimation scheme based on artificial neural networks (ANN) which offers the advantages of increased flexibility to adapt to different environments and high speed parallel processing.
The scheme is developed using a multilayer perceptron neural network (MLP-NN) and set of data (location estimation parameters) that represents some of the characteristics of the transmitted signal between the mobile station and some base stations including angle of arrival (AOA) , time of arrival (TOA) and received signal strength (RSS) as data for training and testing the neural network.
Regarding to location estimation parameters, these data are calculated according to a set of mobile station locations generated randomly.
Also with respect to the received signal strength data were generated according to Hata propagation model for urban environments.
The positioning scheme in this work included seven different cases resulting from the use of the above data, either individually or by merging with each other.
Ten experiments have been made for each case in order to demonstrate the case accuracy by calculating the mean distance error of the estimated locations.
The simulation results showed that for 67% of the estimated locations, the mean distance error for the seven cases (i.e.
RSS, AOA, TOA, RSS / AOA, AOA/TOA, RSS/TOA and RSS/AOA/TOA) is 55.27m, 63.26m, 47.51m 53.15m 42.7m, 39.96m and 41.62m respectively.
All processes were made using MATLAB .
Main Subjects
Information Technology and Computer Science
No. of Pages
116
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : Radio wave propagation models and location estimation methods.
Chapter Three : Neural network scheme for mobile station location estimation.
Chapter Four : Conclusions and future works.
References.
American Psychological Association (APA)
Abd al-Hadi, Qusayy Abd al-Khaliq. (2013). Mobile station location estimation using an artificial neural network (ANN). (Master's theses Theses and Dissertations Master). University of Basrah, Iraq
https://search.emarefa.net/detail/BIM-748051
Modern Language Association (MLA)
Abd al-Hadi, Qusayy Abd al-Khaliq. Mobile station location estimation using an artificial neural network (ANN). (Master's theses Theses and Dissertations Master). University of Basrah. (2013).
https://search.emarefa.net/detail/BIM-748051
American Medical Association (AMA)
Abd al-Hadi, Qusayy Abd al-Khaliq. (2013). Mobile station location estimation using an artificial neural network (ANN). (Master's theses Theses and Dissertations Master). University of Basrah, Iraq
https://search.emarefa.net/detail/BIM-748051
Language
English
Data Type
Arab Theses
Record ID
BIM-748051
