Communications - Scientific Letters of the University of Zilina 2023, 25(3):E15-E23 | DOI: 10.26552/com.C.2023.042

Highly Secure and Accurate Deep Slicing in 5G Wireless Networks for Efficient Resource Utilization

Ambidi Naveena ORCID...
Electronics and Telematics Engineering Department, G. Narayanamma Institute of Technology and Science (for women), Shaikpet, Hyderabad, Telangana, India

Both the current cellular network and the planned 5G mobile network need to meet high dependability standards, very low latency requirements, larger capacity, better security and fast user communication. In order to support multiple independent tenants on the same physical infrastructure, mobile carriers are working towards end-to-end network resource allocation in 5G networks. Future communication networks will require data-driven decision making due to the increase in traffic and the accelerated performance of 5G networks. With the use of in-network deep learning and prediction, a "deep slice" model was built in this study to control network load efficiency and network availability. Even in the event of a network outage, the suggested model is capable of making wise selections and choosing the best network slice.

Keywords: cellular communications, CNN, prediction, network slicing, deep slicing
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The author received no financial support for the research, authorship and/or publication of this article.

Conflicts of interest:

The author declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Received: August 16, 2022; Accepted: February 1, 2023; Prepublished online: April 24, 2023; Published: July 11, 2023  Show citation

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Naveena, A. (2023). Highly Secure and Accurate Deep Slicing in 5G Wireless Networks for Efficient Resource Utilization. Communications - Scientific Letters of the University of Zilina, 25(3), E15-23. doi: 10.26552/com.C.2023.042
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