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Electrical & Computer Engineering Faculty Publications
Document Type
Article
Publication Date
3-20-2003
Abstract
In this paper we use statistical learning theory to evaluate the performance of game theoretic power control algorithms for wireless data in arbitrary channels, i.e., no presumed channel model is required. To show the validity of statistical learning theory in this context, we studied a flat fading channel, and more specifically, we simulated the case of Rayleigh flat fading channel. With the help of a relatively small number of training samples, the results suggest the learnability of the utility function classes defined by changing the user power (adjusted parameter) for each user's utility function.
Publisher
IEEE
Publication Title
2003 IEEE Wireless Communications and Networking
ISSN
1525-3511
Issue
2
First Page
723
Last Page
728
DOI
10.1109/WCNC.2003.1200459
Language (ISO)
English
Sponsorship
IEEE
Keywords
AWGN, Context modeling, Multiaccess communication, Game theory
Recommended Citation
Abdallah, Chaouki T. and M. Hayajneh. "Statistical learning theory to evaluate the performance of game theoretic power control algorithms for wireless data in arbitrary channels." 2003 IEEE Wireless Communications and Networking (2003): 723-728. doi:10.1109/WCNC.2003.1200459.