ABSTRACT
CONTENTS 12.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302
12.1.1 Motivation of Game Theory Based Spectrum Sharing . . . . . . . . . . . . . . . . . . . . . . 302 12.1.2 Spectrum Sharing Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302 12.1.3 Application of Game Theory in Spectrum Sharing . . . . . . . . . . . . . . . . . . . . . . . . . 303
12.1.3.1 Application of Non-cooperative game . . . . . . . . . . . . . . . . . . . . . . . 303 12.1.3.2 Application of cooperative game . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303
12.2 Non-cooperative Spectrum Sharing Game . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304 12.2.1 Network Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304 12.2.2 Pay-off definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305 12.2.3 Power Control for Multi-user Spectrum Sharing Networks . . . . . . . . . . . . . . . . . 305 12.2.4 Distributed Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 306
12.3 Cooperative Spectrum Sharing Game . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307 12.3.1 Network Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307 12.3.2 Cooperative Game Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308 12.3.3 Coalitional Behavior Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 12.3.4 Distributed Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 313
12.4 Spectrum Sharing with Priorities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 313 12.4.1 Network Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 314 12.4.2 The Stackelberg Game Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 314 12.4.3 Distributed Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315
12.1 Introduction 12.1.1 Motivation of Game Theory Based Spectrum Sharing Spectrum sharing is a promising technology to solve the spectrum under-utilization problem for the next generation wireless networking systems. Currently, the optimization of the spectrum sharing system is mainly limited by the following facts: (1) centralized optimization approach for the spectrum sharing network requires collecting the information throughout the entire network, which is inefficient due to the computational and communication complexity; (2) distributed multi-agent optimization problem is notoriously difficult, and there is still a lack of a simple and general framework that can be applied to solve the distributed optimization problem; (3) the spectrum sharing network can be dynamic and time-varying. Simply applying the empirical model or pre-defined policies cannot always guarantee the optimal performance. Most existing works assume the network topology is fixed and the behavior of the wireless device cannot adapt to the changing radio environment.
