Game theory for next generation wireless and communication networks : modeling, analysis, and design / Zhu Han, Dusit Niyato, Walid Saad, Tamer Başar.
Discover the very latest game-theoretic approaches for designing, modeling, and optimizing emerging wireless communication networks and systems with this unique text. Providing a unified and comprehensive treatment throughout, it explains basic concepts and theories for designing novel distributed w...
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Full Text (via Cambridge) |
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| Main Authors: | , , , |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cambridge, United Kigdom ; New York, NY :
Cambridge University Press,
2019.
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| Subjects: |
Table of Contents:
- Cover; Endorsement; Half-Title; Title page; Copyright Information; Dedication; Contents; Acknowledgment; 1 Introduction; 1.1 Overview and Motivation; 1.2 Intended Book Audience; 1.3 Organization; Part I Theory; 2 Matching Games; 2.1 Fundamentals of Matching Theory; 2.1.1 Preliminaries; 2.1.2 Conventional Matching Models; 2.1.3 Wireless-Oriented Matching Models; 2.1.4 Stability and Information Exchange Discussions; 2.2 Example 1: Student Project Allocation Model for LTE-Unlicensed; 2.2.1 LTE-Unlicensed Introduction; 2.2.2 System Model and Problem Formulation
- 2.2.3 The Student Project Allocation Model2.2.4 Matching with Externalities; 2.2.5 Simulation Results and Analysis; 2.2.6 Conclusions; 2.3 Example 2: Stable Fixture Model in LTE V2X; 2.3.1 Basics of LTE V2X; 2.3.2 System Model and Problem Formulation; 2.3.3 Stable Fixture Model; 2.3.4 Simulation Results and Analysis; 2.3.5 Conclusions; 2.4 Summary; 3 Contract Theory; 3.1 Basic Concepts; 3.1.1 Contract Theory: Fundamentals and Classification; 3.1.2 Contract Theory: Reward Design; 3.1.3 Example Scenarios in Wireless Networks
- 3.2 Example 1: Incentive Mechanisms for Device-to-Device Communications in Cellular Networks with Adverse Selection3.2.1 Introduction; 3.2.2 System Model; 3.2.3 Contract-Based Solution; 3.2.4 Simulation Results and Analysis; 3.2.5 Conclusions; 3.3 Example 2: Multidimensional Incentive Mechanism in Mobile Crowdsourcing with Moral Hazard; 3.3.1 Introduction; 3.3.2 System Model; 3.3.3 Problem Formulation; 3.3.4 Simulation Results and Analysis; 3.3.5 Conclusions; 3.4 Example 3: Financing Contract with Adverse Selection and Moral Hazard for Spectrum Trading in Cognitive Radio Networks
- 3.4.1 Introduction3.4.2 Related Works; 3.4.3 System Model; 3.4.4 Problem Formulation; 3.4.5 Discussion; 3.4.6 Simulation Results; 3.4.7 Conclusions; 3.5 Summary; 4 Stochastic Games; 4.1 Basics of a Stochastic Game; 4.2 Strategies, Equilibrium, and Key Results; 4.3 Summary; 5 Games with Bounded Rationality; 5.1 Introduction to Bounded Rationality; 5.2 Prospect Theory: Motivation; 5.3 Foundations of Prospect Theory: Weighting Effects and Framing Effects; 5.3.1 Subjective Players' Actions
- Prospect-Theoretic Weighting Effect
- 5.3.2 Subjective Perceptions of Utility Functions
- The Framing Effect5.3.3 Impact of PT on Game-Theoretic Analysis; 5.4 Other Notions of Bounded Rationality; 5.5 Summary; 6 Learning in Games; 6.1 Introduction to Learning in Games; 6.2 Best Response Dynamics; 6.3 Fictitious Play; 6.4 Regret Matching; 6.5 Reinforcement Learning; 6.6 Learning with Artificial Neural Networks; 6.7 Summary; 7 Equilibrium Programming with Equilibrium Constraints; 7.1 Variational Inequalities; 7.1.1 Basics of Variational Inequalities; 7.1.2 Connections with Optimization and Games; 7.2 Stackelberg Game Review