Channel Selection Based on EWA Game Abstraction in Cognitive Radio Network
Weiheng Jiang · 2010
A priority table of available channels in a network is structured by analyzing channel availability with cooperative spectrum sensing.Using this table,a channel selection learning algorithm based on the experience-weight attraction(EWA) game learning is proposed.Simulations are carried out to compare the learning automata-based algorithm with no-regret learning algorithm.The results show that,by learning historical experience,the algorithm can select channels with the best availability for cognitive users,increase the effective system throughput,and have better equity in resource allocation.