2021
DOI: 10.48550/arxiv.2103.00227
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Towards Intelligent RAN Slicing for B5G: Opportunities and Challenges

EmadElDin A Mazied,
Lingjia Liu,
Scott F. Midkiff

Abstract: To meet the diverse demands for wireless communication, fifth-generation (5G) networks and beyond (B5G) embrace the concept of network slicing by forging virtual instances (slices) of its physical infrastructure. While network slicing constitutes dynamic allocation of core network and radio access network (RAN) resources, this article emphasizes RAN slicing (RAN-S) design. Forming on-demand RAN-S that can be flexibly (re)-configured while ensuring slice isolation is challenging. A variety of machine learning (… Show more

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Cited by 5 publications
(4 citation statements)
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“…For this reason, the focus of this paper is the map of data flow types to specific 5QI slices and its evaluation in a real 5G network with network slicing techniques at the RAN level. It should be noted that the solution presented in this paper is also in line with the core challenges described in [33].…”
Section: Sstsupporting
confidence: 56%
“…For this reason, the focus of this paper is the map of data flow types to specific 5QI slices and its evaluation in a real 5G network with network slicing techniques at the RAN level. It should be noted that the solution presented in this paper is also in line with the core challenges described in [33].…”
Section: Sstsupporting
confidence: 56%
“…Some of these works focus on radio access network (RAN) slicing. Article [11] has addressed the opportunities and challenges of RAN slicing using ML-based techniques. An ensemble learning method-based SAC for adaptive RAN is proposed in [12].…”
Section: Related Workmentioning
confidence: 99%
“…So the publications concentrate on slicing radio access networks (RANs). The advantages and disadvantages of RAN slicing using MLbased algorithms have been discussed in article [11]. In [12], a SAC based on the ensemble learning approach for adaptive RAN is presented.…”
Section: Related Workmentioning
confidence: 99%