Dynamic spectrum trading model for cognitive radio networks
2017-02-15T04:59:54Z (GMT) by
Spectrum frequency is a valuable resource for wireless communication but very limited in its availability. Due to the extensive use and ever increasing demands of unlicensed bands by wireless devices, they are becoming congested, while the licensed bands are found mostly under-utilized. To solve this problem of spectrum scarcity, Cognitive Radio (CR) devices can use licensed bands in many different ways. As reported in academic literature, among various options, the exclusive-use model is the most promising because it provides benefits to both licensed and unlicensed users. In this model, CR enabled service providers, also known as secondary service providers, can buy spectrum from licensed, known as primary service providers, for both a short and long period of time and gain exclusive rights to access the spectrum. The spectrum trading model should depend on several practical factors including pricing of the spectrum, reputation of a seller, duration of the contract and spectrum quality. However, existing pricing models for dynamic spectrum access mainly consider bandwidth which makes these models unsuitable for real-world spectrum trading. In this thesis, a number of innovative approaches on spectrum trading have been introduced particularly considering these practical issues in terms of microeconomic theories. In the first approach, the reputation of spectrum sellers is considered and updated dynamically by considering a buyer’s own trading experience with sellers and collecting recommendations on sellers from other buyers. Trustworthiness of recommenders as well as incentive to encourage recommendations are modeled. In addition to these, contract duration and spectrum quality are incorporated such that a buyer’s utility is formulated as a function of buyer’s resource requirement, reputation of seller, and trustworthiness of recommenders. Finally, the model is analyzed using dynamic pricing of the market and the solution is obtained using market equilibrium. For long term spectrum leasing from primary service providers, a buyer’s reliability is also important for a seller to reduce its risk of profit loss. Therefore, the above developed model is then further extended by incorporating a buyer’s reliability, calculated based on its reputation and credibility scoring. A seller’s experience with a buyer is obtained based on the buyer’s payment completion status, passed time after payment deadline, and percentage of contract completion. As game theory can better capture direct competition among sellers, it is therefore used in our method to model competition among sellers. Once the spectrum is traded, its utilization among secondary users (SUs) under a secondary service provider is essential to improve their throughput. In the post-trading scenario, a dynamic spectrum sharing method is proposed which allows multiple SUs to reside in the same channel and to use it concurrently to maximize the spectrum utilization exploiting variable transmission power of the SUs. The proposed spectrum trading model has been compared with relevant and contemporary methods. The proposed model outperforms existing counterparts in terms of profit for sellers and throughput for buyers, respectively.