ABSTRACT
Contents 15.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 338
15.1.1 Cognitive Radio. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 338 15.1.2 Auction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339 15.1.3 Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 340 15.1.4 Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341
15.2 Game Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341 15.2.1 The Proposed Operating Model of Cognitive Radio . . . . . . . . . . . . . . . . . . . . . . . . . . . 341 15.2.2 Second-Price Auction Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341
15.3 Numerical Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345 15.3.1 Simulation Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345
15.3.1.1 Data Traffic Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345 15.3.1.2 Fading Channel Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345
15.3.2 Nash Equilibrium Establishment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345 15.3.3 Bidder’s Best Budget . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348 15.3.4 Optimal Bidding Slot Length. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348 15.3.5 Supplementary Bidding Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 350 15.3.6 Auctioneer’s Revenue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 351
15.4 Future Work and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 354 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 354
In realization of cognitive radio technology, spectrum utility potential is expected to be fully released, along with the market power. In the future agile spectrum access market, the bargaining between service providers and users will become an inevitable topic as the lines between competition, cooperation, and deviation turn out to be fainter due to the complexity of the network. To deal with dynamic spectrum access from heterogeneous users, the network has to be self-maintainable and the role of the user has to be clearly defined in order for the “game” to play on. This chapter introduces a second-price auction algorithm to address the channel allocation and spectrum access problems for cognitive radio. The Nash equilibrium convergence of the budget-constraint auction and the strategic interactions between auctioneer and secondary users are examined. To cater for the demand of both parties, the implementation issues such as profit maximization, resource utilizationmaximization, and user performancemaximization are also studied. The chapter is concluded by unveiling some open research questions in the application of game-theoretic algorithms.
