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Listen and Talk

Full-duplex Cognitive Radio Networks

  • Book
  • © 2016

Overview

Authors:
  1. Yun Liao

    1. Peking University, Beijing, China

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    You can also search for this author in PubMed   Google Scholar

  2. Lingyang Song

    1. Peking University, Beijing, China

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    You can also search for this author in PubMed   Google Scholar

  3. Zhu Han

    1. Department of Engineering, University of Houston, Houston, USA

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    You can also search for this author in PubMed   Google Scholar

Part of the book series: SpringerBriefs in Electrical and Computer Engineering (BRIEFSELECTRIC)

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Table of contents (5 chapters)

  1. Front Matter

    Pages i-viii
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  2. Introduction

    • Yun Liao, Lingyang Song, Zhu Han
    Pages 1-17

  3. Full-Duplex Cognitive Radio Networks

    • Yun Liao, Lingyang Song, Zhu Han
    Pages 19-50

  4. Extensions of the LAT Protocol

    • Yun Liao, Lingyang Song, Zhu Han
    Pages 51-81

  5. Full-Duplex WiFi

    • Yun Liao, Lingyang Song, Zhu Han
    Pages 83-94

  6. Conclusions and Future Works

    • Yun Liao, Lingyang Song, Zhu Han
    Pages 95-100
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Keywords

About this book

This brief focuses on the use of full-duplex radio in cognitive radio networks, presenting a novel spectrum sharing protocol that allows the secondary users to simultaneously sense and access the vacant spectrum. This protocol, called “Listen-and-talk” (LAT), is evaluated by both mathematical analysis and computer simulations in comparison with other existing protocols, including the listen-before-talk protocol. In addition to LAT-based signal processing and resource allocation, the brief discusses techniques such as spectrum sensing and dynamic spectrum access. 
 
The brief proposes LAT as a suitable access scheme for cognitive radio networks, which can support the quality-of-service requirements of these high priority applications. Fundamental theories and key techniques of cognitive radio networks are also covered.


Listen and Talk: Full-duplex Cognitive Radio Networks is designed for researchers, developers, and professionals involved in cognitive radio networks. Advanced-level students studying signal processing or simulations will also find the content helpful since it moves beyond traditional cognitive radio networks into future applications for the technology.




Authors and Affiliations

  • Peking University, Beijing, China

    Yun Liao, Lingyang Song

  • Department of Engineering, University of Houston, Houston, USA

    Zhu Han

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