# On the Combination of AI and Wireless Technologies: 3GPP Standardization Progress

arXiv: https://arxiv.org/abs/2407.10984 · HTML: https://mlsanity.com/paper/2407.10984/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 20 references that are in the map.
- First posted on arXiv 17 Jun 2024.

## Builds on (most cited first, 4 of 4)

- [Enabling AI in Future Wireless Networks: A Data Life Cycle Perspective](https://mlsanity.com/paper/2003.00866/) (2020)
- [Artificial Intelligence Enabled Wireless Networking for 5G and Beyond: Recent Advances and Future Challenges](https://mlsanity.com/paper/2001.08159/) (2020)
- [AI for CSI Feedback Enhancement in 5G-Advanced](https://mlsanity.com/paper/2206.15132/) (2022)
- [Federated Learning over a Wireless Network: Distributed User Selection through Random Access](https://mlsanity.com/paper/2307.03758/) (2023)

## Built on by (most cited first, 3 of 3)

- [Towards Network Data Analytics in 5G Systems and Beyond](https://mlsanity.com/paper/2506.04860/) (2025)
- [AI/ML in 3GPP 5G Advanced -- Services and Architecture](https://mlsanity.com/paper/2512.03728/) (2025)
- [Contrastive Predictive Coding with Compression for Enhanced Channel State Feedback in Wireless Networks](https://mlsanity.com/paper/2607.05419/) (2026)

## Abstract (arXiv)

Combing Artificial Intelligence (AI) and wireless communication technologies has become one of the major technologies trends towards 2030. This includes using AI to improve the efficiency of the wireless transmission and supporting AI deployment with wireless networks. In this article, the latest progress of the Third Generation Partnership Project (3GPP) standards development is introduced. Concentrating on AI model distributed transfer and AI for Beam Management (BM) with wireless network, we introduce the latest studies and explain how the existing standards should be modified to incorporate the results from academia.