ABSTRACT
Contents 11.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 320
11.1.1 Dynamic WSP Switching with Cognitive Radio . . . . . . . . . 321 11.1.2 Secrecy Capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 322 11.1.3 Pricing Interdependency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 324 11.1.4 Paradigm Shift in CR Network System . . . . . . . . . . . . . . . . . . 324
11.2 Price Motivation in Cognitive Radio Network. . . . . . . . . . . . . . . . . . . . 327 11.3 Pricing-Driven Dynamic Spectrum Allocation. . . . . . . . . . . . . . . . . . . . 328
11.3.1 Types of Auctions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328 11.3.2 Auction Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 11.3.3 Auction Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330 11.3.4 Bidders’ Strategies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331
11.3.4.1 Bidder’s Reservation Price . . . . . . . . . . . . . . . . . . . . . 331 11.3.5 Spectrum Auctioning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332
11.4 Service Provisioning Using Pricing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335 11.4.1 Conflict Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335 11.4.2 Decision Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336 11.4.3 Utility Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336 11.4.4 Price Threshold . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337
11.5 Estimating the Demand for Bandwidth . . . . . . . . . . . . . . . . . . . . . . . . . . . 339 11.6 Secrecy Capacity with Pricing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 340 11.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347
Dynamic spectrum access along with dynamic service offering and profiles are anticipated to increase hugely in the near future, as users move from long-term service provider agreements to more opportunistic service models with the help of cognitive radio (CR) networks. With radio spectrum itself traded as a commodity in a dynamic market-based scenario, wireless service providers (WSPs) will require new strategies to deploy services, define service profiles, and price them. Currently, pricing for dynamic spectrum access in “CR networks” is an open research issue as there is little understanding on how such a dynamic trading system will function so as to make the system feasible under both economic terms and performance.
