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Visual Cognitive Radio

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Wireless Internet (WICON 2011)

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Abstract

Cognitive radio are always based on spectrum sensing to cognize the physical characteristics of the wireless channel and carry out wireless communication resource scheduling. This kind of method has limited predictive ability and cognitive content, which cause it is hard for cognitive radio to response to the change of radio environment in advance. This paper proposes a new system called visual cognitive radio, which use visual information to cognize radio environment. Visual observation has well predictive ability and abundant cognitive information, which enables the visual cognitive radio to deal with the change of radio environment in advance and make optimal configuration to the process of wireless communication. This paper presents a typical communication scene as an example to explain the advantage of visual cognitive radio, and also makes a preliminary analysis of the application and challenge of visual cognitive radio.

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References

  1. Mitola, J.: Cognitive radio architecture evolution. Proceedings of the IEEE 97(4), 626–641 (2009)

    Article  Google Scholar 

  2. Matinmikko, M., Mustonen, M., Sarvanko, H., et al.: A Motivating Overview of Cognitive Radio: Foundations, Regulatory Issues and Key Concepts. VTT Technical Research Centre of Finland, Oulu (February 2008)

    Google Scholar 

  3. Yarkan, S., Arslan, H.: Exploiting Location Awareness toward Improved Wireless System Design in Cognitive Radio. IEEE Communications Magazine 46(1), 128–136 (2008)

    Article  Google Scholar 

  4. Niyato, D., Hossain, E.: Cognitive radio for next-generation wireless networks: an approach to opportunistic channel selection in IEEE 802.11-based wireless mesh. IEEE Wireless Communications 16(1), 46–54 (2009)

    Article  Google Scholar 

  5. MacKenzie, A.B., Reed, J.H., Athanas, P.: Cognitive Radio and Networking Research at Virginia Tech. Proceedings of the IEEE 97(4), 660–688 (2009)

    Article  Google Scholar 

  6. Sharma, R.: Application of MIMO to IFSAR. In: IEEE Radar Conference, Washington, DC, pp. 81–84 (May 2010)

    Google Scholar 

  7. Topsakal, E.: Antennas for medical applications: Ongoing research and future challenges. In: ICEAA Electromagnetics in Advanced Applications, Torino, Italy, pp. 890–893 ( September 2009)

    Google Scholar 

  8. Ito, K.: Recent Small Antennas for Medical Applications. In: International Workshop on Antenna Technology: Small Antennas and Novel Metamaterials, Chiba, Japan, pp. 1–4 (March 2008)

    Google Scholar 

  9. Guida, R., Iodice, A., Riccio, D.: Height Retrieval of Isolated Buildings From Single High-Resolution SAR Images. IEEE Transactions on Geoscience and Remote Sensing 48(7), 2967–2979 (2010)

    Article  Google Scholar 

  10. Hungliu, J., Shijeng, G., Kewu, T., Chili, P.: ECG triggering and gating for ultrasonic small animal imaging. IEEE Ultrasonics, Ferroelectrics and Frequency Control 53(9), 1590–1596 (2006)

    Article  Google Scholar 

  11. Mohajer, M., Rafi, G.Z., Safavi-Naeini, S.: MIMO antenna design and optimization for mobile applications. In: IEEE Antennas and Propagation Society International Symposium, Charleston, USA, pp. 1–4 (June 2009)

    Google Scholar 

  12. Das, S.: Smart antenna design for wireless communication using adaptive beam-forming approach. In: TENCON 2008-2008 IEEE Region 10 Conference, Hyderabad, India, pp. 1–5 (November 2008)

    Google Scholar 

  13. Ariyavisitakul, S.: SIR based power control in a CDMA system. In: Proc. IEEE GLOBECOM, Orlando, USA, pp. 868–873 (December 1992)

    Google Scholar 

  14. Song, L., Mandayam, N., Gajic, Z.: Analysis of an up/down power control algorithm for the CDMA reverse link under fading. IEEE Journal on Selected Areas in Communications 19(2), 277–286 (2001)

    Article  Google Scholar 

  15. Jayaweera, S.K.: Energy efficient virtual MIMO-based cooperative communications for wireless sensor networks. In: International Conference on Intelligent Sensing and Information Processing, Bangalore, India, pp. 1–6 (January 2005)

    Google Scholar 

  16. Nosratinia, A., Hunter, T.E., Hedayat, A.: Cooperative Communication in Wireless Networks. IEEE Communications Magazine 42(10), 74–80 (2004)

    Article  Google Scholar 

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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Liu, T., Ye, D., Shao, S., Tang, Y., Zhou, J. (2012). Visual Cognitive Radio. In: Ren, P., Zhang, C., Liu, X., Liu, P., Ci, S. (eds) Wireless Internet. WICON 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 98. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30493-4_27

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  • DOI: https://doi.org/10.1007/978-3-642-30493-4_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30492-7

  • Online ISBN: 978-3-642-30493-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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