Series on Data Science and Artificial Intelligence for Communications
The objective of the Data Science and Artificial Intelligence for Communications Series of the IEEE Communications Magazine is to provide a forum across industry and academia to advance the development of network and system solutions using data science and artificial intelligence.
Innovations in artificial intelligence, machine learning, reinforcement learning and network data analytics introduce new opportunities in various areas, such as channel modeling and estimation, cognitive communications, interference alignment, mobility management, resource allocation, network control and management, network tomography, multi-agent systems, prioritization of network ultra-broadband deployments. These new analytic platforms will help revolutionize our networks and user experience. Through gathering, processing, learning and controlling the vast amounts of information in an intelligent manner future networks will enable unprecedented automation and optimization.
This Series solicits articles addressing numerous topics within its scope including, but not limited to, the following:
- All aspects of artificial intelligence, machine learning, reinforcement learning and data analytics aiming at enabling and enhancing next generation networks. The scope of issues that can be addressed includes both conventional measures such as traffic management, QoE, service quality, as well as future network behavior through intelligent services and applications.
- Methods, systems and infrastructure for the analysis of network, service traffic and user behavior for efficient and reliable design of networks, including deep learning and statistical methods for network tomography.
- Predictive analytics and artificial intelligence for network optimization, network security, network assurance, and data privacy and integrity. Diagnosis of network failures using analytics and AI.
- Automated communication infrastructure among smart machines and agents (including humans, e.g. speech and vision), and information fusion for automation and enablement of multi-agent systems.
- Communication and networking to facilitate smart data-centric applications
Manuscripts must be submitted through the magazine’s submissions Website at http://mc.manuscriptcentral.com/commag-ieee. You will need to register and then proceed to the author center. On the manuscript details page, please select Data Science and Artificial Intelligence for Communications Series from the drop-down menu. Manuscripts should be tutorial in nature and should not be under review for any other conference or journal. They should be written in a style comprehensible and accessible to readers outside the specialty of the article. Mathematical equations should not be used. For detailed submission guidelines please refer to the magazine website for the list of guidelines that must be followed by all submissions to the IEEE Communications Magazine: https://www.comsoc.org/commag/paper-submission-guidelines
Authors are encouraged to contact the Series Editor before submitting an article in order to ensure that the article will be appropriate for the Series. Papers can be submitted anytime during the year. They will receive a review process, and, if accepted, they will be published in the first slot available for this Series.
- Irena Atov, Microsoft, USA (email@example.com)
- Kwang-Cheng Chen, University of South Florida, USA (firstname.lastname@example.org)
- Shui Yu, University of Technology Sydney, Australia (email@example.com)