# Artificial Intelligence-Enabled Cellular Networks: A Critical Path to Beyond-5G and 6G

arXiv: https://arxiv.org/abs/1907.07862 · HTML: https://mlsanity.com/paper/1907.07862/

## Key facts

- Cited by 25 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Jul 2019.

## Built on by (most cited first, 25 of 25)

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- [AI in 6G: Energy-Efficient Distributed Machine Learning for Multilayer Heterogeneous Networks](https://mlsanity.com/paper/2207.00415/) (2022)
- [Detect to Learn: Structure Learning with Attention and Decision Feedback for MIMO-OFDM Receive Processing](https://mlsanity.com/paper/2208.09287/) (2022)
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- [Distributed Learning Meets 6G: A Communication and Computing Perspective](https://mlsanity.com/paper/2303.12802/) (2023)
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- [Choose, not Hoard: Information-to-Model Matching for Artificial Intelligence in O-RAN](https://mlsanity.com/paper/2208.04229/) (2022)
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- [An Adaptive Framework for Generalizing Network Traffic Prediction towards Uncertain Environments](https://mlsanity.com/paper/2311.18824/) (2023)
- [Attacks Against Mobility Prediction in 5G Networks](https://mlsanity.com/paper/2402.19319/) (2024)
- [Adaptive Anomaly Detection in Network Flows with Low-Rank Tensor Decompositions and Deep Unrolling](https://mlsanity.com/paper/2409.11529/) (2024)
- [DIFFRACT: Neuralized Utility Maximization for Wireless Networks by Differentiable Programming](https://mlsanity.com/paper/2606.07114/) (2026)

## Abstract (arXiv)

Mobile Network Operators (MNOs) are in process of overlaying their conventional macro cellular networks with shorter range cells such as outdoor pico cells. The resultant increase in network complexity creates substantial overhead in terms of operating expenses, time, and labor for their planning and management. Artificial intelligence (AI) offers the potential for MNOs to operate their networks in a more organic and cost-efficient manner. We argue that deploying AI in 5G and Beyond will require surmounting significant technical barriers in terms of robustness, performance, and complexity. We outline future research directions, identify top 5 challenges, and present a possible roadmap to realize the vision of AI-enabled cellular networks for Beyond-5G and 6G.
