Cellular Network Antenna Tilt Anomaly Detection Using Federated Unsupervised Learning

Mulvey, David; Foh, Chuan Heng; Imran, Muhammad Ali; Tafazolli, Rahim

doi:10.1109/icc45041.2023.10279460

ICC 2023 - IEEE International Conference on Communications 2023

DOI: 10.1109/icc45041.2023.10279460

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Cellular Network Antenna Tilt Anomaly Detection Using Federated Unsupervised Learning

David Mulvey,

Chuan Heng Foh,

Muhammad Ali Imran

et al.

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2023

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

Hamdan,

Lee,

Triantafyllopoulou

et al. 2023

Sensors

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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.

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

Hamdan,

Lee,

Triantafyllopoulou

et al. 2023

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

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Cellular Network Antenna Tilt Anomaly Detection Using Federated Unsupervised Learning

Cited by 1 publication

References 10 publications

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

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

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