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We investigate distributed frequency allocation problem in dynamic environment of cognitive radio (CR) networks with a stochastic game (SG) model. Traditional multi-agent reinforcement learning (MARL) algorithms, as the primary online strategy learning algorithms of SG game, are not suitable for the application of wireless communication. Hence, a new MARL algorithm, maximizing the average Q function...
This work on cognitive radio access ventures beyond the more traditional "listen-before-talk" paradigm that underlies many cognitive radio access proposals. We exploit the bi-directional interaction of most primary communication links. By intelligently controlling their access parameters based on the inference from observed link control signals of primary user (PU) communications, cognitive...
The listen-Before-Talk (LBT) strategy has been prevalent in cognitive radio networks where secondary users opportunistically access under-utilized primary band. To minimize the amount of disruption from secondary users to primary signals, secondary users generally are required to detect the presence of the primary user reliably, and access the spectrum intelligently. The sensing time has to be long...
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