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Collaborative Spectrum Trading and Sharing for Cognitive Radio Networks

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Handbook of Cognitive Radio

Abstract

Spectrum trading is one of the most promising approaches to enabling dynamic spectrum access (DSA) in cognitive radio networks (CRNs). With this approach, unlicensed users (a.k.a. secondary users) offer licensed users (a.k.a. primary users) with monetary rewards or improved quality of services (QoSs) in exchange for spectrum access rights. In this chapter, we present a comprehensive introduction to spectrum trading. First, we provide a brief introduction to DSA and CRNs as the background and motivation for the spectrum trading. Then, we present various state-of-the-art spectrum trading mechanisms for spectrum sharing. Finally, by analyzing various design issues in these mechanisms, we introduce the concept of service-oriented spectrum trading and offer a novel collaborative network architecture, called a cognitive mesh assisted network, to effectively utilize unused licensed/unlicensed spectrums with high spectral efficiency. We expect that this chapter provides readers with basic understanding on spectrum trading technology and foster future research initiatives.

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Acknowledgements

This work was partially supported by US National Science Foundation under grants CNS-1343356/CNS-1602172/CNS-1343361, CNS-1409797 and CNS-1423165. The work of M. Pan was also partially supported by US National Science Foundation under grants CNS-1350230 (CAREER) and CPS-1646607. The work of P. Li was also partially supported by US National Science Foundation under grant CNS-1566479 (CAREER). The work of X. Huang was partially supported by the Joint Program of National Science Foundation of China-Guangdong under grants No. U1501255 and No. U1301256. The work of S. Glisic was partially supported by Taseen Käyttö CWC-NS Glisic Menot under 240007101 and ADTEC-2016 Menot under 2410067111.

Author information

Authors and Affiliations

  1. School of Information and Communication Engineering, Dalian University of Technology, 116024, Dalian, Liaoning, China

    Xuanheng Li & Yi Sun

  2. Department of Electrical and Computer Engineering, University of Florida, 32611, 1064 Center Dr., 435 NEB, 116130, Gainesville, FL, USA

    Haichuan Ding & Yuguang Fang

  3. Department of Electrical and Computer Engineering, University of Houston, 77004, 4726 Calhoun Road, W342A, Engineering Building 2, Houston, TX, USA

    Miao Pan

  4. Department of Electrical Engineering and Computer Science, Case Western Reserve University, 44106, 10900 Euclid Avenue,612 Olin, Cleveland, OH, USA

    Pan Li

  5. Shenzhen Institutes of Advanced Technology, China Academy of Sciences, Shenzhen, Guangdong, China

    Xiaoxia Huang

  6. Department of Communication Engineering, University of Oulu, FIN-90014, Erkki Koiso-Kanttilan katu 3, P.O. Box 4500, Oulu, Finland

    Savo Glisic

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  1. Xuanheng Li
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  2. Haichuan Ding
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  3. Yuguang Fang
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  4. Miao Pan
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  5. Pan Li
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  6. Xiaoxia Huang
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  7. Yi Sun
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  8. Savo Glisic
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Correspondence to Pan Li .

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Editors and Affiliations

  1. Electrical Engg Bldg, Rm 325, The University of New South Wales, Sydney, New South Wales, Australia

    Wei Zhang

Section Editor information

  1. Department of Information Engineering, The Chinese University of Hong Kong, Stain, Room 834, Ho Sin Hang Engineering Building, Shatin, New Territory, Hong Kong, China

    Jianwei Huang

  2. School of Data and Computer Science, Sun Yat-Sen University, 510006, Guangzhou, China

    Xu Chen

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Li, X. et al. (2017). Collaborative Spectrum Trading and Sharing for Cognitive Radio Networks. In: Zhang, W. (eds) Handbook of Cognitive Radio . Springer, Singapore. https://doi.org/10.1007/978-981-10-1389-8_27-2

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  • DOI: https://doi.org/10.1007/978-981-10-1389-8_27-2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-1389-8

  • Online ISBN: 978-981-10-1389-8

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Chapter history

  1. Latest

    Collaborative Spectrum Trading and Sharing for Cognitive Radio Networks
    Published:
    11 August 2017

    DOI: https://doi.org/10.1007/978-981-10-1389-8_27-2

  2. Original

    Collaborative Spectrum Trading and Sharing for Cognitive Radio Networks
    Published:
    29 May 2017

    DOI: https://doi.org/10.1007/978-981-10-1389-8_27-1

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