Abstract
Ultra-reliable low-latency communications (URLLC), as one of the three application scenarios of the fifth generation (5G) mobile networks, has attracted extensive attention in the industry. URLLC can play an important role in many scenarios such as traffic safety, remote surgery, and unmanned driving. However, the existing technology is not enough to fully meet its business requirements. Artificial intelligence (AI) is promising to solve the technical problems in the URLLC communication scenario. As a branch of machine learning, deep learning has made a lot of achievements in academia and industry in recent years. It has become one of the landmark technologies of AI. Deep learning can optimize the system end to end, effectively process massive data, and cope with complex channel changes. It is considered as one of the practical tools to deal with physical layer communication. In this article, we first introduce the performance indicators and critical technologies of URLLC in the physical layer. Then we expound on the advantages of deep learning in solving technical problems in the physical layer. Finally, the challenge and opportunity of URLLC based on AI in the sixth-generation (6G) mobile networks are presented.
Original language | English |
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Article number | 9409834 |
Pages (from-to) | 37-43 |
Number of pages | 7 |
Journal | IEEE Communications Standards Magazine |
Volume | 5 |
Issue number | 2 |
DOIs | |
Publication status | Published - Jun 2021 |
Externally published | Yes |
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality
- Computer Networks and Communications
- Law
- Management of Technology and Innovation