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