Please use this identifier to cite or link to this item: https://idr.l4.nitk.ac.in/jspui/handle/123456789/13170
Title: Surrogate modeling based cognitive decision engine for optimization of WLAN performance
Authors: Plets, D.
Chemmangat, K.
Deschrijver, D.
Mehari, M.
Ulaganathan, S.
Pakparvar, M.
Dhaene, T.
Hoebeke, J.
Moerman, I.
Tanghe, E.
Issue Date: 2017
Citation: Wireless Networks, 2017, Vol.23, 8, pp.2347-2359
Abstract: Due to the rapid growth of wireless networks and the dearth of the electromagnetic spectrum, more interference is imposed to the wireless terminals which constrains their performance. In order to mitigate such performance degradation, this paper proposes a novel experimentally verified surrogate model based cognitive decision engine which aims at performance optimization of IEEE 802.11 links. The surrogate model takes the current state and configuration of the network as input and makes a prediction of the QoS parameter that would assist the decision engine to steer the network towards the optimal configuration. The decision engine was applied in two realistic interference scenarios where in both cases, utilization of the cognitive decision engine significantly outperformed the case where the decision engine was not deployed. 2016, Springer Science+Business Media New York.
URI: http://idr.nitk.ac.in/jspui/handle/123456789/13170
Appears in Collections:1. Journal Articles

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