Energy and Spectrum Efficient Wireless Network Design

Erscheinungsjahr 2014
ISBN: 978-1-107-03988-9
Verlag: Cambridge University Press

Buch, Englisch, 400 Seiten, Format (B × H): 179 mm x 254 mm, Gewicht: 930 g

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.

Autoren/Hrsg.

Miao, Guowang

Song, Guocong

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Drahtlostechnologie
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Mobilfunk- und Drahtlosnetzwerke & Anwendungen
• Technische Wissenschaften Energietechnik | Elektrotechnik Energietechnik & Elektrotechnik
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Netzwerksicherheit
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Satellitenkommunikation, Satellitentechnik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Funktechnik
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Signalverarbeitung, Bildverarbeitung, Scanning

Inhaltsverzeichnis

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.

Über Autor(innen)

Miao, Guowang
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.

Song, Guocong
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.