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dc.contributor.authorRojas, C.
dc.contributor.authorDecotignie, J. D.
dc.identifier.citationin 2018 14th International Conference on Wireless and Mobile Computing, Networking and Communications (Issue), ed New York: Ieee, 2018.
dc.description.abstractEstimating the quality of a link is a key primitive in WSNs, as upper layers use this piece of information in making performance-critical decisions. State-of-the-art estimators extract a single sample of the link state per packet. Thus, improving the accuracy through multiple samples requires multiple packets, resulting in a significant energy and traffic overhead and delay. To address this issue, this paper proposes Rep, a novel sampling scheme able to extract the link quality from the packet repetitions of low-power preamble sampling MACs. The experiments show that Rep reduces the energy and traffic used for link estimation by one order of magnitude, and increases the speed of the process by one order of magnitude, while maintaining state-of-the-art accuracy.
dc.titleLeveraging MAC Preambles for an Efficient Link Estimation
dc.typeProceedings Article
dc.type.csemresearchareasIoT & Vision

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