All-Powerful Learning Algorithm for the Priority Access in Cognitive Network

In this paper, we propose the All-Powerful Learning (APL) algorithm for multiple Secondary Users (SUs) that considers the priority access and the dynamic multi-user access, where the number of SUs changes over time. To the best of our knowledge, APL is the first learning algorithm that successfully handles the dynamic users with the priority access. APL does not require any cooperation or prior information (e.g. the number of users in the network, or the number of available channels, or the total number of iterations) as do many existing algorithms. We should emphasize that the knowledge of previous parameters can make all these algorithms impractical and difficult to apply. The experimental results show the superiority of APL compared to existing algorithms.