DocumentCode :
2857473
Title :
A temporal difference method-based prediction scheme applied to fading power signals
Author :
Gao, X.Z.
Author_Institution :
Inst. of Intelligent Power Electron., Helsinki Univ. of Technol., Espoo, Finland
Volume :
3
fYear :
1998
fDate :
4-9 May 1998
Firstpage :
1954
Abstract :
We first briefly discuss the operating principle of the temporal difference (TD) method. A TD method-based multi-step ahead prediction scheme using the modified Elman neural network (MENN) is then set up. This prediction approach provides for online adaptation and fast convergence rate. Next, it is applied to the prediction of the occurrence of long term deep fading in mobile communication systems. Simulation experiments reveal that our prediction scheme is capable of predicting the degree of occurrence possibility of deep fading. Based on this prediction result, the power control of cellular phone systems employing the reinforcement learning method will be investigated in the future
Keywords :
Rayleigh channels; cellular radio; code division multiple access; convergence; fading; feedforward neural nets; learning (artificial intelligence); power control; prediction theory; recurrent neural nets; telecommunication computing; time series; fading power signals; fast convergence rate; long term deep fading; mobile communication systems; modified Elman neural network; online adaptation; temporal difference method-based prediction scheme; Convergence; Fading; Mobile communication; Neural networks; Power electronics; Predictive models; Rayleigh channels; Supervised learning; Uniform resource locators; World Wide Web;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location :
Anchorage, AK
ISSN :
1098-7576
Print_ISBN :
0-7803-4859-1
Type :
conf
DOI :
10.1109/IJCNN.1998.687158
Filename :
687158
Link To Document :
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