Game Theory for Wireless Networks
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Game Theory for Wireless Networks

From Fundamentals to Practice
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Merouane Debbah
849 g
243x197x20 mm

Lasaulce, SamsonSamson received his BSc and Agrégation degree in Applied Physics from École Normale Supérieure (Cachan) and his MSc and PhD in Signal Processing from École Nationale Supérieure des Télécommunications (Paris). Professional experience. He has been working with Motorola Labs for three years (1999, 2000, 2001) and with France Télécom R&D for two years (2002, 2003). Since 2004, he has joined the CNRS and Supélec. Since 2004, he is also Chargé d'Enseignement at École Polytechnique. His broad interests lie in the areas of communications, signal processing and information theory with a special emphasis on game theory for wireless communications. Samson Lasaulce is the recipient of the 2007 ACM/ICST International Conference on Performance Evaluation Methodologies and Tools (VALUETOOLS) and 2009 International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM) best student paper awards. Elena Veronica Belmega, who is a PhD student under my supervision, was awarded with the 2009 Academy of Sciences - L'Oreal - Unesco award for young women in sciences in France.
Written by leading experts in the field, Game Theory and Learning for Wireless Networks Covers how theory can be used to solve prevalent problems in wireless networks such as power control, resource allocation or medium access control. With the emphasis now on promoting 'green' solutions in the wireless field where power consumption is minimized, there is an added focus on developing network solutions that maximizes the use of the spectrum available.

With the growth of distributed wireless networks such as Wi-Fi and the Internet; the push to develop ad hoc and cognitive networks has led to a considerable interest in applying game theory to wireless communication systems. Game Theory and Learning for Wireless Networks is the first comprehensive resource of its kind, and is ideal for wireless communications R&D engineers and graduate students.

Samson Lasaulce is a senior CNRS researcher at the Laboratory of Signals and Systems (LSS) at Supélec, Gif-sur-Yvette, France. He is also a part-time professor in the Department of Physics at École Polytechnique, Palaiseau, France.

Hamidou Tembine is a professor in the Department of Telecommunications at Supélec, Gif-sur-Yvette, France.

Merouane Debbah is a professor at Supélec, Gif-sur-Yvette, France. He is the holder of the Alcatel-Lucent chair in flexible radio since 2007.

The first tutorial style book that gives all the relevant theory, at the right level of rigour, for the wireless communications engineer
Bridges the gap between theory and practice by giving examples and case studies showing how game theory can solve real world resource allocation problems
Contains algorithms and techniques to implement game theory in wireless terminals
One of the big issues in wireless communications systems is power control and interference. Cellular phones located in a certain area need to control their transmission of power to avoid major interference. Power control can be centralized but with increasing customer usage this becomes very complex to control, often leading to inefficiencies. Game theory is considered to be the most powerful tool to realize this important issue of resource allocation. This is the first authored comprehensive and integrated introduction to game theory and its application to wireless communications. Providing the right level of detail for the wireless communications engineer, the book clearly explains the principles of game theory, giving algorithms and techniques, and shows how these can solve the most important problems in wireless resource allocation.
Preface and Introduction.

Part A Games with Complete Information

A1 A short tour of game theory

A2 Playing with equilibria in wireless non-cooperative games

A3 Moving from static to dynamic game

A4 Coalitional games

Part B Games with complete information and learning

B1 Bayesian games

B2 Partially distributed learning algorithms

B3 Fully distributed learning algorithms

Part C Case Studies

C1 Fundamentals of wireless communications

C2 Energy-efficient power control games

C3 Rate-efficient power allocation games

C4 Medium access control games

Part D Appendices

Bibliography and index

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