Self-Organizing Networks for 5G and Beyond: A View from the Top
Future Internet
; 14(3):95, 2022.
Article
in English
| ProQuest Central | ID: covidwho-1760479
ABSTRACT
We describe self-organizing network (SON) concepts and architectures and their potential to play a central role in 5G deployment and next-generation networks. Our focus is on the basic SON use case applied to radio access networks (RAN), which is self-optimization. We analyze SON applications’ rationale and operation, the design and dimensioning of SON systems, possible deficiencies and conflicts that occur through the parallel operation of functions, and describe the strong reliance on machine learning (ML) and artificial intelligence (AI). Moreover, we present and comment on very recent proposals for SON deployment in 5G networks. Typical examples include the binding of SON systems with techniques such as Network Function Virtualization (NFV), Cloud RAN (C-RAN), Ultra-Reliable Low Latency Communications (URLLC), massive Machine-Type Communication (mMTC) for IoT, and automated backhauling, which lead the way towards the adoption of SON techniques in Beyond 5G (B5G) networks.
Computers--Internet; self-organization; self-optimization; self-healing; SON applications and architecture; SON design and dimensioning; machine learning (ML) and artificial intelligence (AI) for SON; massive Machine-Type Communication (mMTC); IoT; URLLC; backhauling; SON for 3G/4G; 5G and B5G networks; Software; Network management systems; Communication; 5G mobile communication; Artificial intelligence; Telecommunications industry; Telecommunications systems; Optimization; Network latency; Internet of Things; Communications networks; Algorithms; Automation; Machine learning; Parallel operation; COVID-19; 51731:Wired and Wireless Telecommunications Carriers; 51121:Software Publishers; 33421:Telephone Apparatus Manufacturing
Full text:
Available
Collection:
Databases of international organizations
Database:
ProQuest Central
Language:
English
Journal:
Future Internet
Year:
2022
Document Type:
Article
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