Robots in the Ether: The Role of Artificial Intelligence and Machine Learning in 5G Radio Access Network and Beyond
5G is already a complex system of over 2,000 parameters. As network slicing, multi-access edge computing (MEC), and ultra-reliable low-latency communications (URLLC) are introduced, the complexity of 5G will increase significantly. In such a complex scenario, artificial intelligence (AI)/machine learning (ML) can make inroads in enhancing radio access network (RAN) operations. The cellular industry began working with AI/ML four to five years ago, starting with 4G Long Term Evolution (LTE). AI/ML in the RAN can be implemented in one of two delivery methods: on top of the RAN and embedded in the RAN.
Please Note: Extended description available upon request.
- Executive Snapshot
- In This Market Note
- IDC's Point of View
- The Role of Virtualization
- Managing Complexity Through AI
- Sustainable Operations
- Why AI/ML in the RAN Is Needed for 5G and Beyond
- AI and ML Models/Algorithms for the RAN
- Learn More
- Synopsis
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