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- W2769459739 abstract "In this paper, we propose a distributed spectrum sensing technique for a finite source of Secondary Users (SUs) in the presence of M Primary Users (PUs) where individual SUs perform spectrum sensing using an Enhanced Blindly Combined Energy Detection (EBCED) technique according to the geometric distribution. We apply graph theory in order to facilitate signal detection using statistical learning and network modeling using random fields. This allows for the defining of neighborhoods for a better network topology through SU collaboration, into forming a non-equilibrium graph model with uniform attachment which has a Poisson degree distribution. Our results indicate that EBCED performs better than the other techniques as it reduces Probability of Mis-Detection (P MD ) by 21.92% compared to conventional energy detection in a distributed scenario. We also show that non-equilibrium graphs can model real-world networks if they use uniform attachment which enhances distance re-use in random fields." @default.
- W2769459739 created "2017-12-04" @default.
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- W2769459739 date "2017-09-01" @default.
- W2769459739 modified "2023-09-28" @default.
- W2769459739 title "Distributed spectrum sensing for cognitive radio systems using graph theory" @default.
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- W2769459739 doi "https://doi.org/10.1109/afrcon.2017.8095493" @default.
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