AI-Native Network Slicing for 6G Networks

By Wen Wu, Conghao Zhou, Mushu Li, Huaqing Wu, Haibo Zhou, Ning Zhang, Xuemin Shen, Weihua Zhuang. IEEE wireless communications, 2021

341 citations recorded by the source corpus.

With the global rollout of fifth generation (5G) networks, it is necessary to look beyond 5G and envision 6G networks. 6G networks are expected to have space-air-ground integrated networks, advanced network virtualization, and ubiquitous intelligence. This article presents an artificial intelligence (AI)-native network slicing architecture for 6G networks to enable the synergy of AI and network slicing, thereby facilitating intelligent network management and supporting emerging AI services. AI-based solutions are first discussed across the network slicing life cycle to intelligently manage network slices (i.e., AI for slicing). Then network slicing solutions are studied to support emerging AI services by constructing AI instances and performing efficient resource management (i.e., slicing for AI). Finally, a case study is presented, followed by a discussion of open research issues that are essential for AI-native network slicing in 6G networks.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, Media Technology

View Paper: https://www.semanticscholar.org/paper/51eaaebdb856096ea5d8fceccd9bf1d40d0ac002

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

  1. Weihua Zhuang
  2. Xuemin Shen
  3. Jie Gao
  4. Mushu Li

In Electrical and Electronic Engineering

  1. Xuemin Shen
  2. Weihua Zhuang
  3. Sinan Gezici
  4. Rongxing Lu
  5. Xiaodong Lin

In Media Technology

  1. Weihua Zhuang

Citations in the corpus