# Machine Learning and Artificial Intelligence in Next-Generation Wireless Network

arXiv: https://arxiv.org/abs/2202.01690 · HTML: https://mlsanity.com/paper/2202.01690/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 47 references that are in the map.
- First posted on arXiv 30 Dec 2021.

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

- [Five Disruptive Technology Directions for 5G](https://mlsanity.com/paper/1312.0229/) (2013)
- [Artificial Neural Networks-Based Machine Learning for Wireless Networks: A Tutorial](https://mlsanity.com/paper/1710.02913/) (2017)
- [When Machine Learning Meets Big Data: A Wireless Communication Perspective](https://mlsanity.com/paper/1901.08329/) (2019)
- [Wireless Communications in the Era of Big Data](https://mlsanity.com/paper/1508.06369/) (2015)

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

- [Efficient Semantic Segmentation on Edge Devices](https://mlsanity.com/paper/2212.13691/) (2022)
- [Data Classification With Multiprocessing](https://mlsanity.com/paper/2312.15152/) (2023)
- [Beyond the Frame: Single and mutilple video summarization method with user-defined length](https://mlsanity.com/paper/2401.10254/) (2023)

## Abstract (arXiv)

Due to the advancement in technologies, the next-generation wireless network will be very diverse, complicated, and according to the changed demands of the consumers. The current network operator methodologies and approaches are traditional and cannot help the next generation networks to utilize their resources most appropriately. The limited capability of the traditional tools will not allow the network providers to fulfill the demands of the network's subscribers in the future. Therefore, this paper will focus on machine learning, automation, artificial intelligence, and big data analytics for improving the capacity and effectiveness of next-generation wireless networks. The paper will discuss the role of these new technologies in improving the service and performance of the network providers in the future. The paper will find out that machine learning, big data analytics, and artificial intelligence will help in making the next-generation wireless network self-adaptive, self-aware, prescriptive, and proactive. At the end of the paper, it will be provided that future wireless network operators cannot work without shifting their operational framework to AI and machine learning technologies.