Using BP Neural Network Algorithm Improve the Prediction Accuracy of Distance between ZigBee

Author

Xuhui, Zhang ; Junfeng, Jia ; Jiaxin, Wei ; Yingjie, Zhao

Author_Institution

Higher Educ. Key Lab. for Meas. & Control Technol. & Instrum. of Heilongjiang Province, Harbin Univ. of Sci. & Technol., Harbin, China

Volume

2

fYear

2011

fDate

28-29 March 2011

Firstpage

790

Lastpage

794

Abstract

This paper proposes that we can improve the accuracy of the distance between ZigBee with the algorithm of BP neural network. Firstly, we analyze the wireless signaling path loss model, the principle of measuring distance based on RSSI, and the algorithm of BP neural network fully. Secondly, we get the experimental data from the hardware platform of ZigBee. Finally, we use the algorithm of BP neural network to emulate and analyze the experimental data. Based on the results of the emulation and analysis, the maximum error of the distance prediction within 120m is 7.62%, with the prediction accuracy improved significantly.

Keywords

Zigbee; backpropagation; neural nets; BP neural network algorithm; RSSI; ZigBee; distance prediction accuracy; wireless signaling path loss model; Accuracy; Arrays; Artificial neural networks; Data models; Measurement uncertainty; Prediction algorithms; Training; Back-Propagation Neural Network; RSSI; ZigBee; the accuracy of distance prediction;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on

Conference_Location

Shenzhen, Guangdong

Print_ISBN

978-1-61284-289-9

Type

conf

DOI

10.1109/ICICTA.2011.485

Filename

5751010