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Conference Papers Year : 2016

Competition: Channel Exploration/Exploitation Based on a Thompson Sampling Approach in a Radio Cognitive Environment

Abstract

Machine learning approaches have been extensively applied in interference mitigation and cognitive radio devices. In this work, we model the spectrum selection process as a multi-arm bandit problem and apply Thompson sampling, a fast and efficient algorithm, to find the best channel in the shortest time interval. The learning algorithm will work on top of a network layer to efficiently route the event information to the sink.
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Dates and versions

hal-01249135 , version 1 (30-12-2015)

Identifiers

  • HAL Id : hal-01249135 , version 1

Cite

Arash Maskooki, Viktor Toldov, Laurent Clavier, Valeria Loscrì, Nathalie Mitton. Competition: Channel Exploration/Exploitation Based on a Thompson Sampling Approach in a Radio Cognitive Environment. EWSN - International Conference on Embedded Wireless Systems and Networks (dependability competition), Feb 2016, Graz, Austria. ⟨hal-01249135⟩
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