Artificial Intelligence to Manage Network Traffic of 5G Wireless Networks

Yu Fu; Sen Wang; Cheng-Xiang Wang; Xuemin Hong; Stephen McLaughlin

doi:10.1109/MNET.2018.1800115

Artificial Intelligence to Manage Network Traffic of 5G Wireless Networks

Yu Fu, Sen Wang, Cheng-Xiang Wang, Xuemin Hong, Stephen McLaughlin

Research output: Contribution to journal › Article › peer-review

103 Citations (Scopus)

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Abstract

The deployment of 5G wireless communication systems is projected to begin in 2020. With new scenarios, new technologies, and new network architectures, the traffic management for 5G networks will present significant technical challenges. In recent years, AI technologies, especially ML technologies, have demonstrated significant success in many application domains, suggesting their potential to help solve the problem of 5G traffic management. In this article, we investigate the new characteristics of 5G wireless network traffic and discuss challenges they present for 5G traffic management. Potential solutions and research directions for the management of 5G traffic, including distributed and lightweight ML algorithms and a novel AI assistant content retrieval algorithm framework, are discussed.

Original language	English
Pages (from-to)	58-64
Number of pages	7
Journal	IEEE Network
Volume	32
Issue number	6
DOIs	https://doi.org/10.1109/MNET.2018.1800115
Publication status	Published - 29 Nov 2018

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abstract = "The deployment of 5G wireless communication systems is projected to begin in 2020. With new scenarios, new technologies, and new network architectures, the traffic management for 5G networks will present significant technical challenges. In recent years, AI technologies, especially ML technologies, have demonstrated significant success in many application domains, suggesting their potential to help solve the problem of 5G traffic management. In this article, we investigate the new characteristics of 5G wireless network traffic and discuss challenges they present for 5G traffic management. Potential solutions and research directions for the management of 5G traffic, including distributed and lightweight ML algorithms and a novel AI assistant content retrieval algorithm framework, are discussed.",

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Artificial Intelligence to Manage Network Traffic of 5G Wireless Networks

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