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Spectrum Sensing Using Markovian Models

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Handbook of Cognitive Radio

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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Acknowledgements

This work was supported in part by the US National Science Foundation under Grants CNS-1421869 and AST-1547329.

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Authors and Affiliations

  1. ECE Department, George Mason University, Fairfax, VA, USA

    Joseph M. Bruno, Yariv Ephraim, Brian L. Mark & Zhi Tian

Authors
  1. Joseph M. Bruno
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  2. Yariv Ephraim
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  3. Brian L. Mark
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  4. Zhi Tian
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Corresponding author

Correspondence to Joseph M. Bruno .

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Editors and Affiliations

  1. School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney, NSW, Australia

    Wei Zhang

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Bruno, J.M., Ephraim, Y., Mark, B.L., Tian, Z. (2019). Spectrum Sensing Using Markovian Models. In: Zhang, W. (eds) Handbook of Cognitive Radio . Springer, Singapore. https://doi.org/10.1007/978-981-10-1394-2_2

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