A Game-Theoretic Approach for Cognitive Radio Networks Using Machine Learning Techniques

Abstract

Cognitive Radio has been viewed as a promising technology to enhance spectrum utilization significantly. In this work, we propose a model for Dynamic Spectrum Allocationin Cognitive Radio Networks using Game Theory. Furthermore, in order to accommodate for all cases, we have put to good use of Preemptive Resume Priority M|M|1 Queuing Model. To supplement it we introduce a priority-based scheduling algorithm called Incremental Weights-Decremental Ratios (IW-DR). As a means to ameliorate the efficiency, we have made use of Regression Models.