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AuthorHashima, Sherief
AuthorFadlullah, Zubair Md
AuthorFouda, Mostafa M.
AuthorMohamed, Ehab Mahmoud
AuthorHatano, Kohei
AuthorElHalawany, Basem M.
AuthorGuizani, Mohsen
Available date2022-10-20T07:53:03Z
Publication Date2022-01-01
Publication NameIEEE Network
CitationHashima, S., Fadlullah, Z. M., Fouda, M. M., Mohamed, E. M., Hatano, K., ElHalawany, B. M., & Guizani, M. (2022). On softwarization of intelligence in 6G networks for ultra-fast optimal policy selection: challenges and opportunities. IEEE Network.‏
AbstractThe emerging Sixth Generation (6G) communication networks promising 100 to 1000 Gbps rates and ultra-low latency (1 millisecond) are anticipated to have native, embedded Artificial Intelligence (AI) capability to support a myriad of services, such as Holographic Type Communications (HTC), tactile Internet, remote surgery, etc. However, these services require ultra-reliability, which is highly impacted by the dynamically changing environment of 6G heterogeneous tiny cells, whereby static AI solutions fitting all scenarios and devices are impractical. Hence, this article introduces a novel concept called the softwarization of intelligence in 6G networks to select the most ideal, ultra-fast optimal policy based on the highly varying channel conditions, traffic demand, user mobility, and so forth. Our envisioned concept is exemplified in a Multi- Armed Bandit (MAB) framework and evaluated within a use case of two simultaneous scenarios (i.e., Neighbor Discovery and Selection (NDS) in a Device-to-Device (D2D) network and aerial gateway selection in an Unmanned Aerial Vehicle (UAV)- based under-served area network). Furthermore, our concept is evaluated through extensive computer-based simulations that indicate encouraging performance. Finally, related challenges and future directions are highlighted.
PublisherInstitute of Electrical and Electronics Engineers Inc.
Subject4G mobile communication systems
TitleOn Softwarization of Intelligence in 6G Networks for Ultra-Fast Optimal Policy Selection: Challenges and Opportunities
dc.accessType Abstract Only

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