Abstract
The wireless networks of the future generation are evolved as complex systems due to broadening in service prerequisites, application heterogeneity and networking of gadgets. In recent times, the major step forward of machine learning techniques is deep learning. However, in wireless/heterogeneous networks, the deep learning application for network traffic control is relatively new. The key disputes in the wireless backbone networks since the advancement of wireless networks are resource allocation and efficient network traffic control such as routing. In larger scale of networks and tangled radio environments, the method of adding intelligence to wireless networks is achieved by Deep Learning (DL). The tangled wireless networks supported with several nodes and their quality of variable link can be investigated by Deep Learning. This paper is presented with a perception of harnessing the next generation communication networks with the artificial neural networks. This work helps the readers to explore the unsolved issues to pursue their research and deeply understand the wireless network design with DL based state of the art facilities. In this work, we integrate the deep learning and wireless networking research with a widespread survey. Finally, this paper summarizes the disputes and benefits of acquiring ML and AI for next generation wireless systems.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: 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.