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Erschienen in:
Multiple Antenna Spectrum Sensing in Colored Noise Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

2. Spectrum Sensing Using Markovian Models

verfasst von : Joseph M. Bruno, Yariv Ephraim, Brian L. Mark, Zhi Tian

Erschienen in: Handbook of Cognitive Radio

Verlag: Springer Singapore

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Abstract

Markovian models, as well as other statistical models, have been applied in the context of cognitive radio communications to characterize user activity in a given spectrum band and to develop algorithms for temporal spectrum sensing. In this chapter, we discuss spectrum sensing based on Markovian models. We provide an overview of the related literature and then discuss the application of discrete-time Markov chain models to spectrum sensing, in particular the hidden bivariate Markov chain. We focus on the modeling of cognitive radio channels using Markov chains, spectrum detection, and parameter estimation. We then discuss various spectrum sensing scenarios in which the Markovian models are used. Finally, we discuss open problems and topics for further research related to spectrum sensing using Markovian models.

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Vorheriges Kapitel Multiple Antenna Spectrum Sensing in Colored Noise
Nächstes Kapitel Waveform Designs for Cognitive Radio and Dynamic Spectrum Access Applications
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Metadaten
Titel
Spectrum Sensing Using Markovian Models
verfasst von
Joseph M. Bruno
Yariv Ephraim
Brian L. Mark
Zhi Tian
Copyright-Jahr
2019
Verlag
Springer Singapore
Buch
Handbook of Cognitive Radio

Print ISBN: 978-981-10-1393-5

Electronic ISBN: 978-981-10-1394-2

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-981-10-1394-2_2

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