Data Rate Prediction in Cognitive Radio by using Self Organizing Maps

This article presents the Learning Algorithm for increasing speed in cognitive radio system. In today-s modern world wireless communications are an effective and efficient way for data transmission. Success of this communication depends on limited radio spectrum. Cognitive radio systems (CRs) are more flexible and used for intelligent spectrum management. However, the processes of a CRs are time consuming. Accordingly, a learning mechanism can increase speed of whole cognition process. This paper introduces a mechanism which is based on the well-known unsupervised learning technique, called Self-Organizing Maps (SOM's), and is used for assisting a CRs to predict the data rate that can be obtained, when it senses specific input data from its environment.