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QoS and Energy Management in Cognitive Radio Network pp 39–95Cite as

Cognitive Radio Network- A Review

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Part of the book series: Signals and Communication Technology ((SCT))

Abstract

As discussed in Chap. 1, the quality of service and energy efficiency of a cognitive radio system depends upon various parameters, including spectrum selection, media access scheme and spectrum sensing order. In this chapter, we provide a review on technologies which facilitates/improves the parameters responsible for QoS and energy management. At the end of this chapter, we will discuss about different cognitive radio platforms and their evolution.

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Notes

  1. 1.

    Here we refer noise as intrinsic noise, which is generated by the communication device itself; while we refer interference as the extrinsic noise, which the communication device receive from other unintended signal sources.

References

  1. FCC. (2003). Revision of parts 2 and 15 of the commissions rules to permit unlicensed national information infrastructure (U-NII) devices in the 5 GHz band. Memorandum opinion and order (Vol. 21).

    Google Scholar 

  2. Atakan, B., & Akan, O. B. (2007). Biologically-inspired spectrum sharing in cognitive radio networks. In 2007 IEEE Wireless Communications and Networking Conference (pp. 43–48).

    Google Scholar 

  3. Eletreby, R. M., Elsayed, H. M., & Khairy, M. M. (2014). Optimal spectrum assignment for cognitive radio sensor networks under coverage constraint. IET Communications, 8(18), 3318–3325.

    Google Scholar 

  4. Niyato, D., Member, S., Hossain, E., & Member, S. (2008). Competitive pricing for spectrum sharing in cognitive radio networks: Dynamic game, inefficiency of nash equilibrium, and collusion. IEEE JSAC, 26(1), 192–202.

    Google Scholar 

  5. Song, Y., Fang, Y., & Zhang, Y. (2007, November). Stochastic channel selection in cognitive radio networks. In Global Telecommunications Conference, 2007. GLOBECOM ’07. IEEE (pp. 4878–4882).

    Google Scholar 

  6. Talat, S., & Wang, L.-C. (2009). Qos-guaranteed channel selection scheme for cognitive radio networks with variable channel bandwidths. In International Conference on Communications, Circuits and Systems, 2009. ICCCAS 2009 (pp. 241–245).

    Google Scholar 

  7. Cai, L. X., Liu, Y., Shen, X., Mark, J. W., & Zhao, D. (2010). Distributed QoS-aware MAC for multimedia over cognitive radio networks. In Global Telecommunications Conference (GLOBECOM 2010), 2010 IEEE (pp. 1–5).

    Google Scholar 

  8. Wang, P., Niyato, D., & Jiang, H. (2010). Voice-service capacity analysis for cognitive radio networks. IEEE Transactions on Vehicular Technology, 59, 1779–1790.

    Google Scholar 

  9. Timmers, M., Pollin, S., Dejonghe, A., Van der Perre, L., & Catthoor, F. (2010). A distributed multichannel MAC protocol for multihop cognitive radio networks. IEEE Transactions on Vehicular Technology, 59, 446–459.

    Article  Google Scholar 

  10. Cordeiro, C., & Challapali, K. (2007). C-MAC: A cognitive MAC protocol for multi-channel wireless networks. In 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2007. DySPAN 2007 (pp. 147–157).

    Google Scholar 

  11. Zhao, Y., Song, M., Xin, C. (2013). FMAC: A fair MAC protocol for coexisting cognitive radio networks. In INFOCOM, 2013 Proceedings IEEE (pp. 1474–1482).

    Google Scholar 

  12. IEEE 802.11 Standard (2012). IEEE 802.11 working group, wireless LAN medium access control (MAC) and physical layer (PHY) specifications.

    Google Scholar 

  13. Le, L., Hossain, E. (2008). A MAC protocol for opportunistic spectrum access in cognitive radio networks. In Wireless Communications and Networking Conference, 2008. WCNC 2008. IEEE (pp. 1426–1430).

    Google Scholar 

  14. Mishra, V., Tong, L. C., Chan, S., & Mathew, J. (2011). MAC protocol for two level QoS support in cognitive radio network. In 2011 International Symposium on Electronic System Design (ISED) (pp. 296–301).

    Google Scholar 

  15. Wang, S., Wang, Y., Coon, J. P., & Doufexi, A. (2012). Energy-efficient spectrum sensing and access for cognitive radio networks. IEEE Transactions on Vehicular Technology, 61, 906–912.

    Google Scholar 

  16. Maleki, S., Pandharipande, A., & Leus, G. (2011). Energy-efficient distributed spectrum sensing for cognitive sensor networks. IEEE Sensors Journal, 11, 565–573.

    Google Scholar 

  17. Liu, Y., Xie, S., Zhang, Y., Yu, R., & Leung, V. C. M. (2012). Energy-efficient spectrum discovery for cognitive radio green networks. Mobile Networks and Applications, 17(1), 64–74.

    Article  Google Scholar 

  18. Gao, S., Qian, L., & Vaman, D. R. (2008). Distributed energy efficient spectrum access in wireless cognitive radio sensor networks. In 2008 IEEE Wireless Communications and Networking Conference (pp. 1442–1447).

    Google Scholar 

  19. Zhang, H., Zhang, Z., Chen, X., & Yin, R. (2011). Energy efficient joint source and channel sensing in cognitive radio sensor networks. In 2011 IEEE International Conference on Communications (ICC) (pp. 1–6).

    Google Scholar 

  20. Zimmermann, A., Günes, M., Wenig, M., Ritzerfeld, J., & Meis, U. (2006). Architecture of the hybrid MCG-mesh testbed. In Proceedings of the 1st International Workshop on Wireless Network Testbeds, Experimental Evaluation and Characterization, WiNTECH ’06 (pp. 88–89). New York: ACM.

    Google Scholar 

  21. Tan, K., Wu, D., Chan, A., & Mohapatra, P. (2010). Comparing simulation tools and experimental testbeds for wireless mesh networks. In 2010 IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks (WoWMoM) (pp. 1–9).

    Google Scholar 

  22. Thompson, J. J., Hopkinson, K. M., & Silvius, M. D. (2015). A test methodology for evaluating cognitive radio systems. IEEE Transactions on Wireless Communications, 14, 6311–6324.

    Google Scholar 

  23. Masonta, M. T., Mzyece, M., & Mekuria, F. (2012). A comparative study of cognitive radio platforms. In Proceedings of the International Conference on Management of Emergent Digital EcoSystems, MEDES ’12 (pp. 145–149). New York: ACM.

    Google Scholar 

  24. Gustafsson, O., Amiri, K., Andersson, D., Blad, A., Bonnet, C., Cavallaro, J. R et al. (2010) Architectures for cognitive radio testbeds and demonstrators 2014; an overview. In 2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications (pp. 1–6).

    Google Scholar 

  25. Lotze, J., Fahmy, S. A., Noguera, J., Doyle, L., & Esser, R. (2008). An FPGA-based cognitive radio framework. In Signals and Systems Conference, 2008. (ISSC 2008). IET Irish (pp. 138–143).

    Google Scholar 

  26. Mitola, J., III, & Maguire, G.Q., Jr. (1999). Cognitive radio: Making software radios more personal. IEEE Personal Communications, 6, 13–18.

    Google Scholar 

  27. Kuon, I., Tessier, R., & Rose, J. (2008). FPGA architecture: Survey and challenges. Foundations and Trends in Electronic Design Automation, 2, 135–253.

    Google Scholar 

  28. Blossom, E. (2004). Gnu radio: Tools for exploring the radio frequency spectrum. Linux Journal, 2004, 4.

    Google Scholar 

  29. SoapySDR Pothosware. (2016) Retrieved April 04, 2016, from http://www.pothosware.com.

  30. Gupta, S., Hunter, C., Murphy, P., & Sabharwal, A. (2009). Warpnet: Clean slate research on deployed wireless networks. In Proceedings of the Tenth ACM International Symposium on Mobile Ad Hoc Networking and Computing, MobiHoc ’09 (pp. 331–332). New York: ACM.

    Google Scholar 

  31. Wickert, M. A., & Lovejoy, M. R. (2015) Hands-on software defined radio experiments with the low-cost RTL-SDR dongle. In Signal Processing and Signal Processing Education Workshop (SP/SPE), 2015 IEEE (pp. 65–70).

    Google Scholar 

  32. RTL-SDR. Retrieved November 01, 2016, from http://www.rtl-sdr.com/about-rtl-sdr.

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Authors and Affiliations

  1. Nanyang Technological University, Singapore, Singapore

    Vishram Mishra & Chiew-Tong Lau

  2. Indian Institute of Technology Patna, Patna, India

    Jimson Mathew

Authors
  1. Vishram Mishra
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  2. Jimson Mathew
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  3. Chiew-Tong Lau
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Correspondence to Vishram Mishra .

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Mishra, V., Mathew, J., Lau, CT. (2017). Cognitive Radio Network- A Review. In: QoS and Energy Management in Cognitive Radio Network. Signals and Communication Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-45860-1_2

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  • DOI: https://doi.org/10.1007/978-3-319-45860-1_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45858-8

  • Online ISBN: 978-3-319-45860-1

  • eBook Packages: EngineeringEngineering (R0)

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