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Energy and Spectrum Efficient Wireless Network Design


  • Date Published: November 2014
  • availability: In stock
  • format: Hardback
  • isbn: 9781107039889

£ 54.00

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About the Authors
  • Covering the fundamental principles and state-of-the-art cross-layer techniques, this practical guide provides the tools needed to design MIMO- and OFDM-based wireless networks that are both energy- and spectrum-efficient. Technologies are introduced in parallel for both centralized and distributed wireless networks to give you a clear understanding of the similarities and differences between their energy- and spectrum-efficient designs, which is essential for achieving the highest network energy saving without losing performance. Cutting-edge green cellular network design technologies, enabling you to master resource management for next-generation wireless networks based on MIMO and OFDM, and detailed real-world implementation examples are provided to guide your engineering design in both theory and practice. Whether you are a graduate student, a researcher or a practitioner in industry, this is an invaluable guide.

    • Provides an in-depth understanding of the similarities and difference between centralized and distributed cross-layer design, essential for achieving optimal network energy efficiency
    • Includes detailed, real-world implementation examples to guide engineering designs in practice
    • Covers state-of-the-art green cellular network design technologies, enabling readers to master resource management for next-generation wireless networks based on MIMO and OFDM
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    Product details

    • Date Published: November 2014
    • format: Hardback
    • isbn: 9781107039889
    • length: 400 pages
    • dimensions: 254 x 179 x 21 mm
    • weight: 0.93kg
    • contains: 122 b/w illus. 20 tables
    • availability: In stock
  • Table of Contents

    1. Introduction
    Part I. Basic Concepts:
    2. Wireless channel properties
    3. Spectral and energy efficiencies of wireless networks
    4. Centralized resource management in wireless networks
    5. Distributed resource management in wireless networks
    Part II. Centralized Cross-Layer Optimization:
    6. Overview
    7. Utility-based optimization framework for OFDMA
    8. Algorithm development for utility-based optimization
    9. Joint channel and queue-aware multicarrier scheduling using delay-based utility functions
    10. Utility-based generalized QoS scheduling for heterogeneous traffic
    11. Asymptotic performance analysis for channel-aware scheduling
    Part III. Distributed Cross-Layer Optimization:
    12. Overview
    13. Opportunistic random access: single-cell cellular networks
    14. Opportunistic random access: any network topology
    15. Optimal channel-aware distributed MAC
    16. Opportunistic random access with intelligent interference avoidance
    17. Distributed power control
    Part IV. Cross-Layer Optimization for Energy-Efficient Networks:
    18. Overview
    19. Energy-efficient transmission
    20. Centralized energy-efficient wireless resource management
    21. Distributed energy-efficient wireless resource management
    22. Energy-efficient cellular network design
    23. Implementation in practice.

  • Authors

    Guowang Miao, Royal Institute of Technology, Stockholm
    Guowang Miao is an Assistant Professor in the Department of Communications Systems at KTH Royal Institute of Technology, Sweden. After receiving his PhD in electrical and computer engineering from Georgia Institute of Technology, USA, in 2009, he spent two years working in industry as a Senior Standard Engineer at Samsung Telecom America. His current research interests are in the design and optimization of wireless communications and networking.

    Guocong Song, ShareThis, California
    Guocong Song is currently Principal Research Engineer at ShareThis, Palo Alto, California. He has been working in wireless communications and networks for a decade, since receiving his PhD in electrical and computer engineering from Georgia Institute of Technology. He received the 2010 IEEE Stephen O. Rice Prize for the best paper in the field of communications theory, and he is recently active in the area of data science and machine learning.

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