NWDAF in 5G: Architecture, Use Cases, and Evolution Across 3GPP Releases

The Network Data Analytics Function (NWDAF) is a pivotal component of the 5G ecosystem, enabling enhanced network intelligence through the analysis of vast amounts of data generated within 5G networks. This paper provides a comprehensive overview of NWDAF, focusing on its architecture, use cases, and evolution across 3GPP releases. It examines NWDAF's role in enabling data-driven decisions for efficient network operation, focusing on the advancements introduced in 3GPP releases 16 and 17. The paper discusses their implications on the current and future capabilities of NWDAF. The paper explores how NWDAF is used in real-world scenarios, highlighting its practical applications. It also looks at the challenges of using NWDAF in complex network setups and points out areas where research is needed to make its implementation more effective. By identifying key research gaps and proposing future directions, this study aims to give a comprehensive overview of NWDAF, highlighting its relevance in advancing intelligent, adaptive, and efficient 5G networks.

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Publication Details

Published
2025-03-06
DOI
https://doi.org/10.1109/ncc63735.2025.10983338
Primary Topic
Telecommunications and Broadcasting Technologies
Type
article
Field-Weighted Citation Impact
0.00
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article

NWDAF in 5G: Architecture, Use Cases, and Evolution Across 3GPP Releases

Shikha Srivastava, Ajay Kumar, Anurag Tiwari, Sanjoy Das
Telecommunications and Broadcasting Technologies
article

NWDAF in 5G: Architecture, Use Cases, and Evolution Across 3GPP Releases

Shikha Srivastava, Ajay Kumar, Anurag Tiwari, Sanjoy Das
article en

Abstract

The Network Data Analytics Function (NWDAF) is a pivotal component of the 5G ecosystem, enabling enhanced network intelligence through the analysis of vast amounts of data generated within 5G networks. This paper provides a comprehensive overview of NWDAF, focusing on its architecture, use cases, and evolution across 3GPP releases. It examines NWDAF's role in enabling data-driven decisions for efficient network operation, focusing on the advancements introduced in 3GPP releases 16 and 17. The paper discusses their implications on the current and future capabilities of NWDAF. The paper explores how NWDAF is used in real-world scenarios, highlighting its practical applications. It also looks at the challenges of using NWDAF in complex network setups and points out areas where research is needed to make its implementation more effective. By identifying key research gaps and proposing future directions, this study aims to give a comprehensive overview of NWDAF, highlighting its relevance in advancing intelligent, adaptive, and efficient 5G networks.

Centre for Development of Telematics (IN)
Openalex Percentile: Top 86%
Telecommunications and Broadcasting Technologies
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