Recent Advances in Machine Learning for Network Automation in the O-RAN

被引：10

作者：

Hamdan, Mutasem Q. ^{[1
]}

Lee, Haeyoung ^{[2
]}

Triantafyllopoulou, Dionysia ^{[3
]}

Borralho, Ruben ^{[4
]}

Kose, Abdulkadir ^{[5
]}

Amiri, Esmaeil ^{[4
]}

Mulvey, David ^{[4
]}

Yu, Wenjuan ^{[6
]}

Zitouni, Rafik ^{[4
]}

Pozza, Riccardo ^{[4
]}

Hunt, Bernie ^{[4
]}

Bagheri, Hamidreza ^{[7
]}

Foh, Chuan Heng ^{[4
]}

Heliot, Fabien ^{[4
]}

Chen, Gaojie ^{[4
]}

Xiao, Pei ^{[4
]}

Wang, Ning ^{[4
]}

Tafazolli, Rahim ^{[4
]}

机构：

[1] Samsung Elect R&D Inst, Staines TW18 4QE, England

[2] Univ Hertfordshire, Sch Phys Engn & Comp Sci, Hatfield AL10 9AB, England

[3] Tech Univ Chemnitz, Professorship Commun Engn, D-09111 Chemnitz, Germany

[4] Univ Surrey, Inst Commun Syst, 5GIC & 6GIC, Guildford GU2 7XH, England

[5] Abdullah Gul Univ, Dept Comp Engn, TR-38080 Kayseri, Turkiye

[6] Univ Lancaster, Sch Comp & Commun, InfoLab21, Lancaster LA1 4WA, England

[7] York St John Univ, Sch Sci Technol & Hlth, York YO31 7EX, England

来源：

SENSORS | 2023年 / 23卷 / 21期

基金：

英国工程与自然科学研究理事会;

关键词：

open radio access networks; machine learning; artificial intelligence; INTELLIGENCE; MOBILE;

D O I：

10.3390/s23218792

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

The evolution of network technologies has witnessed a paradigm shift toward open and intelligent networks, with the Open Radio Access Network (O-RAN) architecture emerging as a promising solution. O-RAN introduces disaggregation and virtualization, enabling network operators to deploy multi-vendor and interoperable solutions. However, managing and automating the complex O-RAN ecosystem presents numerous challenges. To address this, machine learning (ML) techniques have gained considerable attention in recent years, offering promising avenues for network automation in O-RAN. This paper presents a comprehensive survey of the current research efforts on network automation usingML in O-RAN.We begin by providing an overview of the O-RAN architecture and its key components, highlighting the need for automation. Subsequently, we delve into O-RAN support forML techniques. The survey then explores challenges in network automation usingML within the O-RAN environment, followed by the existing research studies discussing application of ML algorithms and frameworks for network automation in O-RAN. The survey further discusses the research opportunities by identifying important aspects whereML techniques can benefit.

引用

页数：35

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