Abstract
In cognitive radio context, spectrum sensing is the vital technique for the cognitive users to acquire the spectrum of frequency band. It requires cognitive users to determine the usage state of the spectrum through spectrum perception and access the spectrum for communication when the spectrum is idle. However, the accuracy of single radio spectrum is low. Thus, the proposed algorithm adopts the joint Long and Short Term Memory (LSTM) and Convolutional Neural Network (CNN) as the prediction model for a combined design, which is used for spectrum prediction under multi-channel toward spectrum sharing. The simulation results show that the sensing accuracy of the radio spectrum is significantly improved.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
