Evolutionary Network Slice Association Algorithm For Load Balancing In Heterogeneous Open Radio Access Networks

Citation

Anwar Ridwan, Uwais Al-Qarni and Chuah, Teong Chee and Lee, Ying Loong (2024) Evolutionary Network Slice Association Algorithm For Load Balancing In Heterogeneous Open Radio Access Networks. Journal of Engineering Science and Technology., 19 (1). pp. 335-350. ISSN 1823-4690

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Abstract

The problem of user association (UA) for a network slicing-enabled heterogeneous network deployed under an Open Radio Access Network (ORAN) architecture is investigated in this paper. Efficient UA is crucial for achieving load balance among network slices (NSs) and preventing overloading or underutilisation. UA is challenging in such networks because user equipment (UE) establishes wireless connectivity through NSs virtualised at the open radio units, creating a three-level association relationship. The UA problem is first formulated to maximise a generalised fairness utility function subject to constraints on NS resources and UE quality of service. To solve this computationally hard integer-programming problem, the constraints are converted into penalty functions that transform the constrained problem into an unconstrained one. A genetic algorithm (GA) is then designed to solve the unconstrained problem. Simulation results demonstrate that the proposed scheme outperforms baseline schemes in terms of load balance and quality of service fulfilment. Our work highlights the critical importance of efficient UA in heterogeneous networks with network slicing deployed under the O-RAN architecture and provides a promising framework for future research in this area.

Item Type: Article
Uncontrolled Keywords: Genetic algorithm, Heterogeneous networks, Network slicing, O-RAN, User association.
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 04 Mar 2024 02:22
Last Modified: 04 Mar 2024 02:22
URII: http://shdl.mmu.edu.my/id/eprint/12174

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