Machine Learning for 5G Communications and Beyond

Dear Colleagues,

Machine learning has recently gained importance due to the increased availability of data and computing power. Its application to mobile and wireless communication technologies is in an infant state; however, it is generally agreed that machine learning will be a key element to enable new applications and to increase efficiency. In fact, for 5G and beyond, machine learning is considered of paramount importance to provide low latency and high reliability. In addition, network operators expect great benefits from machine learning with regard to the design, control and optimization of networks. To get the most of machine learning, wireless networks will undergo many changes in its architecture, protocol stacks, data formats, etc. We invite researchers to contribute original papers describing the application and impact of machine learning in 5G communications and beyond. Potential topics include, but are not limited to, the following:

Machine learning in radio interface protocols

Machine learning for network operation and management

Machine learning in software defined networking (SDN) and network function virtualization (NFV)

Machine learning for spectrum management

Machine learning for resource allocation

Machine learning for Massive MIMO

Machine learning for green communications

Machine learning for prediction of subscriber behavior

Machine learning and self-organizing networks (SON)

Machine learning for Internet of things (IoT)

Machine learning for vehicular communications

Dr. David Martín-Sacristán
Dr. Sandra Roger
Guest Editors

Manuscript Submission Information

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