Improved Learning Scheme for Cognitive Radio using Artificial Neural Networks - Rita Mahajan; Deepak Bagai (International Journal of Electrical and Computer Engineering (IJECE), 2016)
The future of wireless system is facing the problem of spectrum scarcity. Number of users is increasing rapidly but available spectrum is limited. The Cognitive Radio (CR) network technology can enable the unlicensed users to share the frequency spectrum with the licensed users on a dynamic basis without creating any interference to primary user. Whenever secondary user finds that primary user is not transmitting and channel is free then it uses channel opportunistically. In this paper cognitive radio with predictive capability using artificial neural network has been proposed. The advantage of such cognitive user is saving of time and energy for spectrum sensing. Proposed radio will sense only that channel which is predicted to be free and channel is selected on the basis of maximum vacant time. Performance has been evaluated in the term of mean square error. The results show that this learning capability can be embedded in secondary users for better performance of future wireless technologies.