Improving the Performance of Cognitive Radios Through Classification, Learning, and Predictive Channel Selection
Prediction of future idle times of different channels based on history information allows a Cognitive Radio (CR) to select the best channels for control and data transmission. In contrast to earlier work, the proposed method works not only with a specific type of traffic but learns and classifies the traffic type of each channel over time and can select the prediction method based on that. Different prediction rules apply to partially deterministic and stochastic ON-OFF patterns. New prediction methods for both traffic classes are developed in the paper. A CR predicts how long the channels are going to be idle. The channel with the longest predicted idle time is selected for secondary use.