GPRS Congestion Control Algorithm Based on Fuzzy Kernel Neural Networks

Author

Su, J.L. ; Chen, Yimin ; Ouyang, Zhonghui

Author_Institution

Sch. of Comput. Eng. & Sci., Shanghai Univ.

Volume

1

fYear

2006

fDate

16-18 Oct. 2006

Firstpage

954

Lastpage

959

Abstract

An algorithm of fuzzy optimization design based on neural networks is presented as a new method for GPRS congestion control. The combination system adopts a new fuzzy neuron network which can appropriately adjust input and output, and increase robustness, stability and working speed of the network. Besides FNN, wavelet transform also be applied to compression algorithm for a higher and controllable compression rate. As shown by experimental results, the algorithm is capable of significantly preventing the congestion control, which proves that it is a more practical and more effective method than traditional methods for congestion control in wireless networks, and it is especially better at video data transmitting

Keywords

fuzzy neural nets; fuzzy set theory; optimisation; packet radio networks; telecommunication congestion control; wavelet transforms; GPRS congestion control; compression algorithm; fuzzy kernel neural network; fuzzy neuron network; fuzzy optimization design; robustness; stability; wavelet transform; Algorithm design and analysis; Design optimization; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Ground penetrating radar; Kernel; Neural networks; Neurons; Robust stability; FNN; GPRS; congestion control; wavelet transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on

Conference_Location

Jinan

Print_ISBN

0-7695-2528-8

Type

conf

DOI

10.1109/ISDA.2006.164

Filename

4021568