# Artificial Intelligence Enabled Wireless Networking for 5G and Beyond: Recent Advances and Future Challenges

arXiv: https://arxiv.org/abs/2001.08159 · HTML: https://mlsanity.com/paper/2001.08159/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Jan 2020.

## Built on by (most cited first, 9 of 9)

- [Holistic Network Virtualization and Pervasive Network Intelligence for 6G](https://mlsanity.com/paper/2301.00519/) (2023)
- [On the Combination of AI and Wireless Technologies: 3GPP Standardization Progress](https://mlsanity.com/paper/2407.10984/) (2024)
- [Learning Autonomy in Management of Wireless Random Networks](https://mlsanity.com/paper/2106.07984/) (2021)
- [Defensive Distillation based Adversarial Attacks Mitigation Method for Channel Estimation using Deep Learning Models in Next-Generation Wireless Networks](https://mlsanity.com/paper/2208.10279/) (2022)
- [Low PAPR MIMO-OFDM Design Based on Convolutional Autoencoder](https://mlsanity.com/paper/2301.05017/) (2023)
- [Unsupervised ANN-Based Equalizer and Its Trainable FPGA Implementation](https://mlsanity.com/paper/2304.06987/) (2023)
- [Federated Learning over a Wireless Network: Distributed User Selection through Random Access](https://mlsanity.com/paper/2307.03758/) (2023)
- [Multi-Agent Feedback Enabled Neural Networks for Intelligent Communications](https://mlsanity.com/paper/2205.10750/) (2022)
- [Magmaw: Modality-Agnostic Adversarial Attacks on Machine Learning-Based Wireless Communication Systems](https://mlsanity.com/paper/2311.00207/) (2023)

## Abstract (arXiv)

The fifth generation (5G) wireless communication networks are currently being deployed, and beyond 5G (B5G) networks are expected to be developed over the next decade. Artificial intelligence (AI) technologies and, in particular, machine learning (ML) have the potential to efficiently solve the unstructured and seemingly intractable problems by involving large amounts of data that need to be dealt with in B5G. This article studies how AI and ML can be leveraged for the design and operation of B5G networks. We first provide a comprehensive survey of recent advances and future challenges that result from bringing AI/ML technologies into B5G wireless networks. Our survey touches different aspects of wireless network design and optimization, including channel measurements, modeling, and estimation, physical-layer research, and network management and optimization. Then, ML algorithms and applications to B5G networks are reviewed, followed by an overview of standard developments of applying AI/ML algorithms to B5G networks. We conclude this study by the future challenges on applying AI/ML to B5G networks.