@InCollection{Shams2021, author = {Nakisa Shams and Hadi Amirpour and Christian Timmerer and Mohammad Ghanbari}, booktitle = {Proceedings of Sixth International Congress on Information and Communication Technology}, publisher = {Springer Singapore}, title = {{A Channel Allocation Algorithm for Cognitive Radio Users Based on Channel State Predictors}}, year = {2021}, month = {sep}, pages = {711--719}, volume = {235}, abstract = {Cognitive radio networks can efficiently manage the radio spectrum by utilizing the spectrum holes for secondary users in licensed frequency bands. The energy that is used to detect spectrum holes can be reduced considerably by predicting them. However, collisions can occur either between a primary user and secondary users or among the secondary users themselves. This paper introduces a centralized channel allocation algorithm (CCAA) in a scenario with multiple secondary users to control primary and secondary collisions. The proposed allocation algorithm, which uses a channel state predictor (CSP), provides good performance with fairness among the secondary users while they have minimal interference with the primary user. The simulation results show that the probability of a wrong prediction of an idle channel state in a multi-channel system is less than 0.9%. The channel state prediction saves the sensing energy by 73%, and the utilization of the spectrum can be improved by more than 77%.}, doi = {10.1007/978-981-16-2380-6_62}, keywords = {Cognitive radio, Neural networks, Prediction, Idle channel}, url = {https://link.springer.com/chapter/10.1007/978-981-16-2380-6_62} }