NDLI: A new indoor location technology using back propagation neural network to fit the RSSI-d curve

Content Provider	IEEE Xplore Digital Library
Author	Huiqing Zhang Xiaowei Shi
Copyright Year	2012
Description	Author affiliation: College of Electronic Information and Control Engineering, Beijing University of Technology, 100124, China (Huiqing Zhang; Xiaowei Shi)
Abstract	After lots of research and analysis of the RSSI-d(received signal strength indicator RSSI and distanced) relationship between the reference nodes and blind nodes, A new indoor WLAN location technology using BP neural network to fit the RSSI-d curve is proposed. Firstly, establish a three-layer BP neural network, the input layer of the network is RSSI, through the hidden layer processing, the final output from the output layer is distance d between the reference node and blind node. Once get three more such distance d, according to the known coordinates of the reference nodes, Taylor series expansion algorithm is used to determine the coordinates of the blind node. Finally, the experiment result shows that the new algorithm improves the positioning accuracy and universality, compared with the traditional positioning algorithms.
Starting Page	80
Ending Page	83
File Size	415285
Page Count	4
File Format	PDF
ISBN	9781467313971
e-ISBN	9781467313988
DOI	10.1109/WCICA.2012.6357843
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Taylor series Algorithm design and analysis Biological neural networks Wireless communication Educational institutions Accuracy Taylor Series Indoor location WLAN Back propagation neural network RSSI
Content Type	Text
Resource Type	Article

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