A Quadrilateral Geometry Classification Method and Device for Femtocell Positioning NetworksReportar como inadecuado


A Quadrilateral Geometry Classification Method and Device for Femtocell Positioning Networks


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1

Department of Communications Engineering, Yuan-Ze University, Taoyuan 320, Taiwan

2

Communication Research Center, Yuan-Ze University, Taoyuan 320, Taiwan





*

Author to whom correspondence should be addressed.



Academic Editors: Cheng-Chi Wang and Ming-Tsang Lee

Abstract This article proposes a normalization multi-layer perception NMLP geometry classifier to autonomously determine the optimal four femtocell evolved Node Bs FeNBs, which can use time difference of arrival TDOA to measure the location of the macrocell user equipment MUE with the lowest GDOP value. The iterative geometry training IGT algorithm is designed to obtain the training data for the NMLP geometry classifier. The architecture of the proposed NMLP geometry classifier is realized in the server of the cloud computing platform, to identify the optimal geometry disposition of four FeNBs for positioning the MUE located between two buildings. Six by six neurons are chosen for two hidden layers, in order to shorten the convergent time. The feasibility of the proposed method is demonstrated by means of numerical simulations. In addition, the simulation results also show that the proposed method is particularly suitable for the application of the MUE positioning with a huge number of FeNBs. Finally, three quadrilateral optimum geometry disposition decision criteria are analyzed for the validation of the simulation results. View Full-Text

Keywords: femtocell positioning network; optimum geometry disposition decision criteria; normalization multi layer perception; iterative geometry training algorithm; time difference of arrival; cloud computing platform femtocell positioning network; optimum geometry disposition decision criteria; normalization multi layer perception; iterative geometry training algorithm; time difference of arrival; cloud computing platform





Autor: Jeich Mar 1,2,* , Tsung Yu Chang 1 and Yu Jie Wang 1

Fuente: http://mdpi.com/



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