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Sensors 2012, 12(3), 2798-2817; doi:10.3390/s120302798

Artificial Neural Network for Location Estimation in Wireless Communication Systems

Department of Information Management, Tainan University of Technology, No. 529, Jhongjheng Rd., Yongkang Dist., Tainan 71002, Taiwan
Received: 12 January 2012 / Revised: 22 February 2012 / Accepted: 23 February 2012 / Published: 1 March 2012
(This article belongs to the Special Issue Collaborative Sensors)
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In a wireless communication system, wireless location is the technique used to estimate the location of a mobile station (MS). To enhance the accuracy of MS location prediction, we propose a novel algorithm that utilizes time of arrival (TOA) measurements and the angle of arrival (AOA) information to locate MS when three base stations (BSs) are available. Artificial neural networks (ANN) are widely used techniques in various areas to overcome the problem of exclusive and nonlinear relationships. When the MS is heard by only three BSs, the proposed algorithm utilizes the intersections of three TOA circles (and the AOA line), based on various neural networks, to estimate the MS location in non-line-of-sight (NLOS) environments. Simulations were conducted to evaluate the performance of the algorithm for different NLOS error distributions. The numerical analysis and simulation results show that the proposed algorithms can obtain more precise location estimation under different NLOS environments. View Full-Text
Keywords: time of arrival (TOA); angle of arrival (AOA); non-line-of-sight (NLOS); artificial neural networks (ANN) time of arrival (TOA); angle of arrival (AOA); non-line-of-sight (NLOS); artificial neural networks (ANN)

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Chen, C.-S. Artificial Neural Network for Location Estimation in Wireless Communication Systems. Sensors 2012, 12, 2798-2817.

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