NDLI: Enhanced Signal-Strength-Difference Position Method Based on an Inversion Propagation Model in Cellular Network

Content Provider	IEEE Xplore Digital Library
Author	Li Xu Yuhao Wang Ye Liu Ming Wei Yang Si
Copyright Year	2008
Description	Author affiliation: Dept. of Electron. Inf. Eng., Nanchang Univ., Nanchang (Li Xu; Yuhao Wang; Ye Liu; Ming Wei; Yang Si)
Abstract	This paper develops a simple and efficient position method based on relative signal-strength prediction, which can be got from an inversion propagation model in cellular networks. The inversion propagation model can predict the propagation loss between any two points along the virtual propagation path from the base-station to mobile-station, which precision has been presented in. So the user's location can be predicted by matching the average signal-strength-difference of the neighboring list in the mobile phone to the coverage prediction differences from multiple base-stations in the appointed area. The effectiveness of the proposed method has been demonstrated by using experiments under various radio environments in Guang Dong, China. It was shown that the enhanced signal-strength-difference position method can locate the user with about the accuracy of 150 m in 67 percentage and 300 m in 92 percentage respectively. Despite the result not meeting Federal Communications Commission (FCC) requirements, this method proved to be sufficiently simple and efficient in terms of the computation at burden and network signaling load.
Starting Page	1
Ending Page	4
File Size	150584
Page Count	4
File Format	PDF
ISBN	9781424421077
DOI	10.1109/WiCom.2008.444
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wireless sensor networks Navigation Land mobile radio cellular systems Senior citizens FCC Predictive models Position measurement Propagation losses Mobile handsets Computer networks
Content Type	Text
Resource Type	Article

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