Mobile Position Estimation using Artificial Neural Network in CDMA Cellular Systems

  • Omar Waleed Abdulwahhab, Ass. Prof. Dr. College of Engineering-University of Baghdad
  • Sally Antoin Jergees College of Engineering-University of Baghdad
Keywords: feed forward neural network, time of arrival, received signal strength, back propagation, optimal positioning method, and average positioning method.

Abstract

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The results show that the neural network has good performance compared with two other analytical methods which are average positioning method and optimal positioning method.

 

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Published
2016-01-01
How to Cite
Abdulwahhab, O. and Jergees, S. (2016) “Mobile Position Estimation using Artificial Neural Network in CDMA Cellular Systems”, Journal of Engineering, 22(1), pp. 83-102. Available at: http://joe.uobaghdad.edu.iq/index.php/main/article/view/273 (Accessed: 6April2020).

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