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A Belief-Based Decision-Making Framework for Spectrum Selection in Cognitive Radio Networks

Perez-Romero, J, Raschella, A, Sallent, O and Umbert, A (2016) A Belief-Based Decision-Making Framework for Spectrum Selection in Cognitive Radio Networks. IEEE Transactions on Vehicular Technology, 65 (10). pp. 8283-8296. ISSN 1939-9359

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This paper presents a comprehensive cognitive management framework for spectrum selection in cognitive radio (CR) networks. The framework uses a belief vector concept as a means to predict the interference affecting the different spectrum blocks (SBs) and relies on a smart analysis of the scenario dynamicity to properly determine an adequate observation strategy to balance the tradeoff between achievable performance and measurement requirements. In this respect, the paper shows that the interference dynamics in a given SB can be properly characterized through the second highest eigenvalue of the interference state transition matrix. Therefore, this indicator is retained in the proposed framework as a relevant parameter to drive the selection of both the observation strategy and spectrum selection decision-making criterion. This paper evaluates the proposed framework to illustrate the capability to properly choose among a set of possible observation strategies under different scenario conditions. Furthermore, a comparison against other state-of-the-art solutions is presented.

Item Type: Article
Uncontrolled Keywords: 09 Engineering, 08 Information And Computing Sciences, 10 Technology
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computer Science & Mathematics
Publisher: IEEE
Related URLs:
Date Deposited: 03 Feb 2017 12:42
Last Modified: 04 Sep 2021 11:59
DOI or ID number: 10.1109/TVT.2015.2508646
URI: https://researchonline.ljmu.ac.uk/id/eprint/5435
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