Deep Learning Empowered Spectrum Sensing and Access in Distributed Cognitive Radio Network
TimeTuesday, July 12th6pm - 7pm PDT
LocationLevel 2 Lobby
Event Type
Networking Reception
Work-in-Progress Poster
DescriptionThis paper addresses the communication efficiency in blockchain from the perspective of dynamic spectrum allocation and proposes a Deep Learning-empowered Cooperative Spectrum Sensing and Access (DL-CS2A) model in distributed Cognitive Radio Networks (CRN).
Convolutional Neural Network and Gate Recurrent Unit are combined for distributed cooperative spectrum sensing.
Besides, we propose a hard decision method that performs linear weighting based on user reputation.
After spectrum sensing, dynamic spectrum access technology is adopted to select the appropriate access time and frequency band for data transmission.
Simulation results indicate that the proposed deep learning-driven CRN system can effectively improve the communication efficiency.