Fu, Y., Wang, S., Wang, C.X., Hong, X. and McLaughlin, S. (2018) Artificial Intelligence to Manage Network Traffic of 5G Wireless Networks. IEEE Network, 32, 58-64.
https://doi.org/10.1109/MNET.2018.1800115

has been cited by the following article:

• TITLE: Artificial Intelligence Self-Organising (AI-SON) Frameworks for 5G-Enabled Networks: A Review

  AUTHORS: Delali Kwasi Dake

  KEYWORDS: Self-Organising Networks, Artificial Intelligence, Software-Defined Networks, 5G Networks, Big Data

  JOURNAL NAME: Journal of Computer and Communications, Vol.11 No.4, April 25, 2023

  ABSTRACT: The fifth generation (5G) networks will support the rapid emergence of Internet of Things (IoT) devices operating in a heterogeneous network (HetNet) system. These 5G-enabled IoT devices will result in a surge in data traffic for Mobile Network Operators (MNOs) to handle. At the same time, MNOs are preparing for a paradigm shift to decouple the control and forwarding plane in a Software-Defined Networking (SDN) architecture. Artificial Intelligence powered Self-Organising Networks (AI-SON) can fit into the SDN architecture by providing prediction and recommender systems to minimise costs in supporting the MNO’s infrastructure. This paper presents a review report on AI-SON frameworks in 5G and SDN. The review considers the dynamic deployment and functions of the AI-SON frameworks, especially for SDN support and applications. Each module in the frameworks was discussed to ascertain its relevance based on the context of AI-SON and SDN integration. After examining each framework, the identified gaps are summarised as open issues for future works.