Learning Nash Equilibria in Distributed Channel Selection for Frequency-Agile Radios
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2012Access:
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I. Macaluso, L. A. DaSilva, and L. E. Doyle, Learning Nash Equilibria in Distributed Channel Selection for Frequency-Agile Radios, ECAI 2012 Workshop on Artificial Intelligence for Telecommunications and Sensor Networks, Montpellier, France, 27-31 August, 2012, 2012, 7 - 10Download Item:
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Abstract:
Wireless communication networks are evolving towards self-
configuring, autonomous and distributed multiagent systems in
which nodes are deployed randomly and have to adapt to the en-
vironment in which they operate. A cognitive network is a self-
organising system that relies on the ability of its autonomous
nodes to support communication in an adaptive and distributed
manner. In this paper we address the distributed channel selec-
tion problem, which is a crucial component of many cognitive
networks scenario, in the context of frequency-agile radios that
are able to operate in multiple frequency bands simultaneously.
We formulate the problem as an N-player stochastic game with
incomplete information. We prove that by adopting a simple
reinforcement scheme, namely learning automata, nodes will
converge to a Nash equilibrium, under the assumption of sym-
metric interference between the players
Sponsor
Grant Number
Science Foundation Ireland (SFI)
10/CE/I1853
Author's Homepage:
http://people.tcd.ie/dasilvalhttp://people.tcd.ie/macalusi
http://people.tcd.ie/ledoyle
Description:
PUBLISHEDMontpellier, France
Other Titles:
ECAI 2012 Workshop on Artificial Intelligence for Telecommunications and Sensor NetworksType of material:
Conference PaperAvailability:
Full text availableKeywords:
Wireless NetworksSubject (TCD):
TelecommunicationsLicences: