# Towards Network Data Analytics in 5G Systems and Beyond

arXiv: https://arxiv.org/abs/2506.04860 · HTML: https://mlsanity.com/paper/2506.04860/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 36 references that are in the map.
- First posted on arXiv 5 Jun 2025.

## Builds on (most cited first, 5 of 5)

- [Towards Supporting Intelligence in 5G/6G Core Networks: NWDAF Implementation and Initial Analysis](https://mlsanity.com/paper/2205.15121/) (2022)
- [On the Combination of AI and Wireless Technologies: 3GPP Standardization Progress](https://mlsanity.com/paper/2407.10984/) (2024)
- [An NWDAF Approach to 5G Core Network Signaling Traffic: Analysis and Characterization](https://mlsanity.com/paper/2209.10428/) (2022)
- [A Model Drift Detection and Adaptation Framework for 5G Core Networks](https://mlsanity.com/paper/2209.06852/) (2022)
- [Hierarchical Network Data Analytics Framework for B5G Network Automation: Design and Implementation](https://mlsanity.com/paper/2309.16269/) (2023)

## Abstract (arXiv)

Data has become a critical asset in the digital economy, yet it remains underutilized by Mobile Network Operators (MNOs), unlike Over-the-Top (OTT) players that lead global market valuations. To move beyond the commoditization of connectivity and deliver greater value to customers, data analytics emerges as a strategic enabler. Using data efficiently is essential for unlocking new service opportunities, optimizing operational efficiency, and mitigating operational and business risks. Since Release 15, the 3rd Generation Partnership Project (3GPP) has introduced the Network Data Analytics Function (NWDAF) to provide powerful insights and predictions using data collected across mobile networks, supporting both user-centric and network-oriented use cases. However, academic research has largely focused on a limited set of methods and use cases, driven by the availability of datasets, restricting broader exploration. This study analyzes trends and gaps in more than 70 articles and proposes two novel use cases to promote the adoption of NWDAF and explore its potential for monetization.