A Thompson Sampling Approach to Channel Exploration-Exploitation Problem in Multihop Cognitive Radio Networks

Viktor Toldov 1, 2, 3 Laurent Clavier 3, 4 Valeria Loscrí 1 Nathalie Mitton 1
3 CSAM
IEMN - Institut d’Électronique, de Microélectronique et de Nanotechnologie (IEMN) - UMR 8520, Institut TELECOM/TELECOM Lille1, IRCICA - Institut de Recherche sur les Composants logiciels et matériels pour l'Information et la Communication Avancé
Abstract : Cognitive radio technology is a promising solution to the exponential growth in bandwidth demand sustained by increasing number of ubiquitous connected devices. The allocated spectrum is opened to the secondary users conditioned on limited interference on the primary owner of the band. A major bottleneck in cognitive radio systems is to find the best available channel quickly from a large accessible set of channels. This work formulates the channel exploration-exploitation dilemma as a multi-arm bandit problem. Existing theoretical solutions to a multi-arm bandit are adapted for cognitive radio and evaluated in an experimental test-bed. It is shown that a Thompson sampling based algorithm efficiently converges to the best channel faster than the existing algorithms and achieves higher asymptotic average throughput. We then propose a multihop extension together with an experimental proof of concept.
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Viktor Toldov, Laurent Clavier, Valeria Loscrí, Nathalie Mitton. A Thompson Sampling Approach to Channel Exploration-Exploitation Problem in Multihop Cognitive Radio Networks. 27th annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Sep 2016, Valencia, Spain. ⟨hal-01355002⟩

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