Interference Constraint Active Learning with Uncertain Feedback for Cognitive Radio Networks

In this paper, an intelligent probing method for interference constraint learning is proposed to allow a centralized cognitive radio network (CRN) to access the frequency band of a primary user (PU) in an underlay cognitive communication scenario. The main idea is that the CRN probes the PU and subs...

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Veröffentlicht in:	IEEE transactions on wireless communications Jg. 16; H. 7; S. 4654 - 4668
Hauptverfasser:	Tsakmalis, Anestis, Chatzinotas, Symeon, Ottersten, Bjorn
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.07.2017 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Active learning Bayes methods Bayesian active learning Bayesian analysis Cognitive radio Computer simulation cutting plane methods Feedback Interference Interference channels Interference constraints Learning probabilistic bisection algorithm Probabilistic methods Probability theory Radio networks Sensors Signal to noise ratio cutting plane methods Bayesian active learning Bayes methods Interference channels Sensors probabilistic bisection algorithm Cognitive radio Interference constraints Signal to noise ratio
ISSN:	1536-1276, 1558-2248, 1558-2248
Online-Zugang:	Volltext
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