Cognitive Radio Spectrum Decision Based on Channel Usage Prediction

The paper is about a new strategy suggested for spectrum decision in Cognitive Radio (CR) networks. By jointly considering sensing error, Secondary Users (SUs) competition and SUs transmission collision, a new parameter called Channel Usage State (CUS) is introduced. For a particular channel, we predict the respective probabilities of occurrence of CUS states by using the LeZi-update scheme. We also adopt a fuzzy comparison algorithm to combine the prediction results as a joint value. The largest joint value is associated with the most available channel for access by SUs in the near future. By comparing with random channel access, the suggested strategy can improve SUs transmission throughput. This is demonstrated by the simulation evaluations