DocumentCode :
3578285
Title :
WSN Location Method Based on BP Neural Network in NLOS Environment
Author :
Yue Yu ; Ling-Hua Zhang
Author_Institution :
Coll. of Telecommun. & Inf. Eng., Nanjing Univ. of Posts & Telecommun., Nanjing, China
fYear :
2014
Firstpage :
321
Lastpage :
325
Abstract :
Given to the non-line-of-sight (NLOS) error existing in the location of wireless sensor network (WSN), together with the strong anti-noise ability, good data approximation and flexible parallel data processing ability of BP neural network, the method of using BP neural network to optimize the location of WSN nodes is put forward in this paper. Firstly, the source of error is analyzed. Then the traditional BP neural network is optimized on the structure and the algorithm to improve the convergence speed. Finally reliable nodes are used to train the neural network. The trained neural network is applied to fulfill the location of unknown nodes. Meanwhile, the simulation results show that this method can effectively suppress NLOS error and its location precision is superior to the traditional Taylor algorithm and Chan algorithm.
Keywords :
backpropagation; interference suppression; neural nets; parallel processing; telecommunication computing; telecommunication network reliability; wireless sensor networks; BP neural network training; NLOS error suppression; WSN location method; antinoise ability; data approximation; flexible parallel data processing; non-line-of-sight error; wireless sensor network reliability; Algorithm design and analysis; Biological neural networks; Convergence; Reliability; Training; Wireless sensor networks; BP neural network; NLOS; WSN; location precision; training algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless Communication and Sensor Network (WCSN), 2014 International Conference on
Print_ISBN :
978-1-4799-7090-2
Type :
conf
DOI :
10.1109/WCSN.2014.72
Filename :
7061748
Link To Document :
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