Seleção dinâmica de Canais de Controle em Rádios Cognitivos utilizando Reinforcement Learning

Raphael M. GuedesJosé Ferreira de Rezende

Cognitive radios have emerged as a promising technology in spectrumsharing among secondary users (SUs). Due to difficulties faced by this solution,many proposals consider the existence of a channel, called control channel.Through this channel SUs can exchange coordination messages. However,due to a number of factors, it is unlikely that a single control channel is simultaneouslyavailable to all SUs. One solution is to use a multi-channel approach,where nodes can hop from channel to channel in order to find other users toexchange information. Thus, there must be a channel sequence, which most ofusers can communicate. This paper discusses the use of Reinforcement Learningas a possible tool for discovering those channel sequences.

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Biblioteca Digital Brasileira de Computação - Contato:
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