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Sequential Learning and Decision-Making in Wireless Resource Management

  • Book
  • © 2016

Overview

Authors:
  1. Rong Zheng

    1. Department of Computing, McMaster University, Hamilton, Canada

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    You can also search for this author in PubMed   Google Scholar

  2. Cunqing Hua

    1. School of Information Security Engineering, Shanghai Jiao Tong University, Shanghai, China

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    You can also search for this author in PubMed   Google Scholar

  • Emphasizes intuition rather than laborious proofs
  • Provides a recipe for applying theoretical tools to real-world problems
  • Treats both theoretical and practical aspects of the sequential learning and decision making framework
  • Covers many representative applications in wireless networks
  • Includes supplementary material: sn.pub/extras

Part of the book series: Wireless Networks (WN)

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Table of contents (8 chapters)

  1. Front Matter

    Pages i-xiii
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  2. Theory

    1. Front Matter

      Pages 1-1
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    2. Introduction

      • Rong Zheng, Cunqing Hua
      Pages 3-7

    3. Stochastic Multi-armed Bandit

      • Rong Zheng, Cunqing Hua
      Pages 9-25

    4. Markov Multi-armed Bandit

      • Rong Zheng, Cunqing Hua
      Pages 27-39

    5. Adversarial Multi-armed Bandit

      • Rong Zheng, Cunqing Hua
      Pages 41-57

  3. Applications

    1. Front Matter

      Pages 59-59
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    2. Spectrum Sensing and Access in Cognitive Radio Networks

      • Rong Zheng, Cunqing Hua
      Pages 61-69

    3. Sniffer-Channel Assignment in Multichannel Wireless Networks

      • Rong Zheng, Cunqing Hua
      Pages 71-90

    4. Online Routing in Multi-hop Wireless Networks

      • Rong Zheng, Cunqing Hua
      Pages 91-101

    5. Channel Selection and User Association in WiFi Networks

      • Rong Zheng, Cunqing Hua
      Pages 103-115

  4. Back Matter

    Pages 117-118
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Keywords

About this book

This book lays out the theoretical foundation of the so-called multi-armed bandit (MAB) problems and puts it in the context of resource management in wireless networks. Part I of the book presents the formulations, algorithms and performance of three forms of MAB problems, namely, stochastic, Markov and adversarial. Covering all three forms of MAB problems makes this book unique in the field. Part II of the book provides detailed discussions of representative applications of the sequential learning framework in cognitive radio networks, wireless LANs and wireless mesh networks. 


Both individuals in industry and those in the wireless research community will benefit from this comprehensive and timely treatment of these topics. Advanced-level students studying communications engineering and networks will also find the content valuable and accessible.




Authors and Affiliations

  • Department of Computing, McMaster University, Hamilton, Canada

    Rong Zheng

  • School of Information Security Engineering, Shanghai Jiao Tong University, Shanghai, China

    Cunqing Hua

Bibliographic Information

  • Book Title: Sequential Learning and Decision-Making in Wireless Resource Management

  • Authors: Rong Zheng, Cunqing Hua

  • Series Title: Wireless Networks

  • DOI: https://doi.org/10.1007/978-3-319-50502-2

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer International Publishing AG 2016

  • Hardcover ISBN: 978-3-319-50501-5Published: 12 January 2017

  • Softcover ISBN: 978-3-319-84413-8Published: 07 July 2018

  • eBook ISBN: 978-3-319-50502-2Published: 05 January 2017

  • Series ISSN: 2366-1186

  • Series E-ISSN: 2366-1445

  • Edition Number: 1

  • Number of Pages: XIII, 118

  • Number of Illustrations: 22 b/w illustrations

  • Topics: Computer Communication Networks, Communications Engineering, Networks

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