Title:
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AI-Based Autonomous Control, Management, and Orchestration in 5G: From Standards to Algorithms
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Author:
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Banchs, Albert; Bega, Dario; Costa, Xavier; Fiore, Marco; Gramaglia, Marco; Petez, Ramon
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Abstract:
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While the application of artificial intelligence (Ai) to 5G networks has raised strong interest, standard solutions to bring Ai into 5G systems are still in their infancy and have a long way to go before they can be used to build an operational system. in this article, we contribute to bridging the gap between standards and a working solution by defining a framework that brings together the relevant standard specifications and complements them with additional building blocks. We populate this framework with concrete Ai-based algorithms that serve different purposes toward developing a fully operational system. We evaluate the performance resulting from applying our framework to control, management, and orchestration functions, showing the benefits that Ai can bring to 5G systems. |
Publication date:
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2020-12-02 |
Subject(s):
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AI-Driven Systems Artificial Intelligence & Big Data 5G & Internet of Things |
Rights:
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© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Pages:
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7 p. |
Document type:
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Article Article - Published version |
DOI:
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10.1109/MNET.001.2000047
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Published by:
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IEEE
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Publish at:
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IEEE Network
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Collection:
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Volume 34;Issue 6
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Share:
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