Abstract
This paper reviews cognitive radio spectrum sensing techniques. With high demand for wireless communications, there is a lack of spectrum resources due to the fixed use policy. The idea of cognitive radio (CR) networks has been the subject of numerous research works as a way of utilizing spectrum resources efficiently. Spectrum sensing (SS) techniques have been proposed, and effective spectrum utilization methods have been established. Deep learning techniques for spectrum sensing have been proven to be better than conventional techniques when combined with cognitive radio technology. A review and comparison of the merits and drawbacks of each technique are given. A description of the use of deep learning techniques in spectrum sensing is given next. Lastly, the challenges of deep learning techniques and potential areas of future research are reviewed.