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Cognitive Radio Networks

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Cognitive Technologies

Part of the book series: Telecommunications and Information Technology ((TIT))

Abstract

A cognitive radio can be defined by the capability of being aware of its environment and the internal state and, based on the knowledge of these elements and any stored pre-defined objectives, can dynamically adapt, make, and implement decisions about its behavior. Among the applications of cognitive radio, the most widely explored regards the improvement of spectrum bands usage, also known as white spaces. This paper presents a review of cognitive radio framework that facilitates the understanding and implementation of spectrum management functions of a typical-cognitive radio network project.

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References

  1. Dahrouj H, Al-naffouri TY, Alouini H. Elsawy MS (2015) Virtualized cognitive network architecture for 5G cellular networks. IEEE Commun Mag 53(7):78–85

    Google Scholar 

  2. McHenry M (2003) Spectrum white space measurements. New Am Found Broadband Forum, Meas

    Google Scholar 

  3. Maguire GQ, Mitola J (1999) Cognitive radio: making software radios more personal. IEEE Pers Commun 6, 13–18

    Google Scholar 

  4. Federal Communications Commission, (2003) Et docket-322

    Google Scholar 

  5. Cui S, Sayed AH, Quan Z (2008) Optimal linear cooperation for spectrum sensing in cognitive radio networks. IEEE J Sel Topics Signal Proces 2(1):28–40

    Google Scholar 

  6. Tong L, Swami A, Chen Y, Zhao Q (2007) Decentralized cognitive MAC for for opportunistic spectrum access in ad hoc networks a POMDP framework. IEEE J Sel Areas Commun 25(3):589–600

    Google Scholar 

  7. Mishra SM, Brodersen R, Cabric D (2004) Implementation issues in spectrum sensing for cognitive radios. In: 38th Asilomar conference signals, systems and computers, Pacific Grove, CA, pp 772–776

    Google Scholar 

  8. Kay SM (1998) Fundamentals of statistical signal processing: detection theory. Prentice-Hall, Englewood Cliffs, NJ

    Google Scholar 

  9. Tkachenko A, Brodersen RW, Cabric D (2006) Experimental study of spectrum sensing based on energy detection and network cooperation. In: ACM 1st workshop on technology and policy for accessing spectrum (TAPAS)

    Google Scholar 

  10. Cochran D, Enserink S (1994) A cyclostationary feature detector. In: 28th Asilomar conference on signals, systems, and computers, Monterrey- CA, pp 806–810

    Google Scholar 

  11. Haykin S (2005) Cognitive radio: brain-empowered wireless communications. IEEE J Sel Areas Commun 23:201–220

    Article  Google Scholar 

  12. Lee W-Y, Chowdhury KR, Akyildiz IF (2009) CRAHNs: cognitive radio ad hoc networks. Ad Hoc Netw 7:810–836

    Article  Google Scholar 

  13. Lee W-Y, Vuran MC, Shantidev M, Akyildiz IF (2006) NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey. Comput Netw J 50:2127–2159

    Google Scholar 

  14. Ramchandran K, Wild B (2005) Detecting primary receivers for cognitive radio applications. In: IEEE DySPAN, pp 124–130

    Google Scholar 

  15. FCC (2003) Notice of inquiry task force report. ET Docket

    Google Scholar 

  16. Mishra SM, Brodersen RW, Cabric D (2004) Imlementation issues in spectrum sensing for cognitive radios. In: IEEE conference on signals, systems and computers, Asilomar, pp 772–776

    Google Scholar 

  17. Whitt W, Sriram K (1986) Characterizing superposition arrival processes in packet multiplexers for voice and data. IEEE J Sel Areas Commun 4(6):833–846

    Article  Google Scholar 

  18. Mousavinia A, Amirpour H, Shamsi N (2013) A channel state prediction for multi-secondary users in a cognitive radio based on neural network. In: 2013 international conference on electronics, computer and computation (ICECCO), Ankara, pp 200–203

    Google Scholar 

  19. Yin SX, Hong W, Li SF, Yin L (2011) Spectrum behavior learning in cognitive radio based on artificial neural network. In: 2011-MILCOM military communications conference, Baltimore, MD, pp 25–30

    Google Scholar 

  20. Taj MI, Akil M (2011) Cognitive radio spectrum evolution prediction using artificial neural networks based multivariate time series modelling. In: Wireless conference 2011-sustainable wireless technologies (European wireless), 11th European, Vienna, Austria, pp 1–6

    Google Scholar 

  21. Neel J (2006) Analysis and design of cognitive radio networks and distributed radio resource management algorithms. PhD Dissertation, Virginia Polytechnic Institute and State University

    Google Scholar 

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Correspondence to D. Carrillo .

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Carrillo, D. (2017). Cognitive Radio Networks. In: Paradisi, A., Godoy Souza Mello, A., Lira Figueiredo, F., Carvalho Figueiredo, R. (eds) Cognitive Technologies. Telecommunications and Information Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-53753-5_8

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  • DOI: https://doi.org/10.1007/978-3-319-53753-5_8

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-53753-5

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