Spectrum sharing using deep learning: multi-agent reinforcement learning

The number of people using cell phones and the requirement for the radio band has increased over the last few years. The fast rise of 5G networks for wireless communication and wireless communication has met this need. There is reason to believe that the issue of improper use of the wireless spectrum could be resolved with the progress of cognitive radio and its spectrum-sensing technology. Deep learning technology is known for being able to learn and change amazingly quickly. The purpose of this research is to provide a brief summary of the approach used in cognitive radio spectrum-sensing technology and deep learning technology. The first part of this study talks about the common spectrum-sensing methods to give a big picture of the benefits of deep learning-based spectrum-sensing algorithms. We find that our method can increase the accuracy of previous work and conventional learning strategies by as much as 83%.