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Intelligent Spectrum Handoff via Docitive Learning in Cognitive Radio Networks (CRNs)

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Technical Report,01 Dec 2012,01 Sep 2016

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University of Alabama at Tuscaloosa Tuscaloosa United States

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In this project, we target the design of a Docitive Learning also called transfer learning based spectrum handoff design in Cognitive Radio Networks CRNs. If the current channel quality is below a threshold, the secondary user SU should make one of the following decisions 1 stay in the same channel and wait for it to become idle again this strategy is called wait-and-stay, 2 stay in the same channel and adjust the channel parameters according to the varying channel conditions this strategy is called stay-and-adjust, or 3 switch to another idle channel that meets its QoS requirement this is the conventional spectrum handoff. In this project, we have applied a critic-based transfer learning model to implement an intelligent spectrum handoff with both node-to-node learning and self-learning. Additionally, a multi-teacher-based transfer learning scheme is used to learn handoff parameters from multiple neighbors. We have also built a comprehensive CRN testbed for spectrum handoff test. Such a testbed has other essential CRN components, such as spectrum sensing, mining and handoff.

Subject Categories:

  • Radio Communications
  • Computer Systems

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