Abstract
In beamformed wireless cellular systems such as 5G New Radio (NR) networks, beam management (BM) is a crucial operation. In the second phase of 5G NR standardization, known as 5G-Advanced, which is being vigorously promoted, the key component is the use of artificial intelligence (AI) based on machine learning (ML) techniques. AI/ML for BM is selected as a representative use case. This article provides an overview of the AI/ML for BM in 5G-Advanced. The legacy non-AI and prime AI-enabled BM frameworks are first introduced and compared. Then, the main scope of AI/ML for BM is presented, including improving accuracy, reducing overhead and latency. Finally, the key challenges and open issues in the standardization of AI/ML for BM are discussed, especially the design of new protocols for AI-enabled BM. This article provides a guideline for the study of AI/ML-based BM standardization.
Cite
CITATION STYLE
Xue, Q., Guo, J., Zhou, B., Xu, Y., Li, Z., & Ma, S. (2024). AI/ML for Beam Management in 5G-Advanced: A Standardization Perspective. IEEE Vehicular Technology Magazine, 19(4), 64–72. https://doi.org/10.1109/MVT.2024.3431790
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