Vol. 1 No. 3 (2021): Beyond 5G Communications

Artificial Intelligence - The Announced Revolution in Communications

Mehdi Bennis
University of Oulu, Finland
Rui Campos
INESC TEC, Faculty of Engineering of the University of Porto
Capa artigo Artificial Intelligence - The Announced Revolution in Communications

Published 2021-12-09

How to Cite

Bennis, M., & Campos, R. (2021). Artificial Intelligence - The Announced Revolution in Communications. INESC TEC Science&Society, 1(3). Retrieved from https://science-society.inesctec.pt/index.php/inesctecesociedade/article/view/ai_the_announced_revolution_in_communications


Artificial Intelligence (AI) is currently changing our everyday life in multiple domains, be it in the form of personal assistants, autonomous cars, or smart texting. This powerful technology will now be embedded in the communications networks that are the nervous system of the digital world in which we are immersed. AI will indeed be crucial for next generation networks. It will be there by design and enable network self-management and self-control towards fully autonomous networks operating similarly to other autonomous systems such as autonomous cars and autonomous aircrafts. For example, through AI the creation of the so-called network slices in 5G – i.e., application-oriented virtual networks over the physical infrastructure – will be fully autonomous, towards the intent-based networking paradigm envisioned for 6G.

The need for AI in next generation networks comes from the ever-increasing complexity of the underlying technologies, including an ever-increasing number of parameters that can be controlled and whose optimization according to the networking context is yet to be explored. Also, there is a need for making networks efficient and scalable from multiple perspectives including performance, energy consumption and privacy. This complexity leads to an increasing need for holistic solutions that take advantage of AI techniques and of the available computational capacity, either in the cloud or in the edge, as the only means to self-optimize the network operation dynamically and in real-time.


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