A Review of Machine learning Use-Cases in Telecommunication Industry in the 5G Era
Mahmoud, Haitham and Ismail, Tawfik (2021) A Review of Machine learning Use-Cases in Telecommunication Industry in the 5G Era. In: 16th International Computer Engineering Conference (ICENCO), 29th - 30th December 2020, Cairo, Egypt.
| Preview | Text 5G_paper_HM.pdf - Accepted Version Download (706kB) | 
Abstract
With the development of the 5G and Internet of things (IoT) applications, which lead to an enormous amount of data, the need for efficient data-driven algorithms has become crucial. Security concerns are therefore expected to be raised using state-of-the-art information technology (IT) as data may be vulnerable to remote attacks. As a result, this paper provides a high-level overview of machine-learning use-cases for data-driven, maintaining security, or easing telecommunications operating processes. It emphasizes the importance of analyzing the role of machine learning in the telecommunications sector in terms of network operation.
| Item Type: | Conference or Workshop Item (Paper) | 
|---|---|
| Identification Number: | 10.1109/ICENCO49778.2020.9357376 | 
| Dates: | Date Event 1 December 2020 Accepted 24 February 2021 Published Online | 
| Uncontrolled Keywords: | Machine-learning, Telecommunications industry, Artificial intelligence | 
| Subjects: | CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science | 
| Divisions: | Architecture, Built Environment, Computing and Engineering > Computer Science | 
| Depositing User: | Gemma Tonks | 
| Date Deposited: | 13 Nov 2023 16:43 | 
| Last Modified: | 13 Nov 2023 16:43 | 
| URI: | https://www.open-access.bcu.ac.uk/id/eprint/14933 | 
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