A Game Based Energy Sensitive Spectrum Auction Model and Bid Learning Process for Cognitive Radio Systems

Abstract

An auction based bid learning process for cognitive radio networks, where the users and the service providers are learning about each other to maximise each other's utility is examined. A game model is formulated to allow players to learn depending on their priority. This enables users to learn different parameters such as the best offered bid price and the appropriate time to participate in the auction process. The performance of the system is examined based on the developed utility function. The results show that the blocking probability, utility function and the energy consumed is better with the learning users when compared to the non-learning users. Results also show that provided learning is taking place in the system, Nash Equilibrium can be established.