Spectrum sensing techniques in cognitive wireless sensor networks

Abstract : In this thesis we investigate the required efficiency and reliability trade-off of spectrum sensing techniques in cognitive wireless sensor networks (CWSNs). An overview of the developed spectrum sensing techniques in the literature is provided. Then, considering the challenges posed by the framework of resource-constrained nodes in CWSNs, we propose several improved local and cooperative methods for spectrum sensing. Firstly, in order to minimize the channel observation duration and to get reduced power consumption, the problem of running the spectrum sensing process from a small sample size is addressed. We thus propose two techniques in order to increase the strength of the decision on the presence or not of a signal: local spectrum sensing based on the goodness-of-fit (GoF) principle and cooperative spectrum sensing based on the Dempster- Shafer (D-S) theory of evidence. Moreover, considering the energy efficiency of the whole network and the reliability of the decision, a robust and energy efficient cooperative spectrum sensing scheme is proposed. This latter is based on a clustering algorithm and utilizes a double reliability evaluation. Compared with the methods in the literature, the proposed method present an improved performance of detection, and is designed to support harsh channel conditions and faulty nodes.
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Submitted on : Friday, November 18, 2016 - 1:09:54 PM
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  • HAL Id : tel-01399124, version 1


Shaoyang Men. Spectrum sensing techniques in cognitive wireless sensor networks. Electronics. UNIVERSITE DE NANTES, 2016. English. ⟨tel-01399124⟩



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