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AI-Based Autonomous Control, Management, and Orchestration in 5G: From Standards to Algorithms

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ieeenet_banchs.pdf (433.3Kb)
Identifiers
URI: http://hdl.handle.net/20.500.12761/928
DOI: 10.1109/MNET.001.2000047
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Author(s)
Bega, Dario; Gramaglia, Marco; Pérez, Ramón; Fiore, Marco; Banchs, Albert; Costa-Perez, Xavier
Date
2020-12-02
Abstract
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.
Share
Files
ieeenet_banchs.pdf (433.3Kb)
Identifiers
URI: http://hdl.handle.net/20.500.12761/928
DOI: 10.1109/MNET.001.2000047
Metadata
Show full item record

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