AI for CSI Feedback Enhancement in 5G-Advanced

被引：14

作者：

Guo, Jiajia ^{[1
]}

Wen, Chao-Kai ^{[2
]}

Jin, Shi ^{[1
]}

Li, Xiao ^{[1
]}

机构：

[1] Southeast Univ, Nanjing, Peoples R China

[2] Natl Sun Yat sen Univ, Inst Commun Engn, Kaohsiung, Taiwan

来源：

IEEE WIRELESS COMMUNICATIONS | 2024年 / 31卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Artificial intelligence; Precoding; Standardization; Downlink; 5G mobile communication; Complexity theory; 3GPP;

D O I：

10.1109/MWC.010.2200304

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

The 3rd Generation Partnership Project began studying Release 18 in 2021. Artificial intelligence (AI)-native air interface is one of the key features of Release 18, where AI for channel state information (CSI) feedback enhancement is selected as the representative use case. This article provides an overview of AI for CSI feedback enhancement in 5G-Advanced. Several representative non-AI and AI-enabled CSI feedback frameworks are introduced and compared. Then, the standardization of AI for CSI feedback enhancement in 5G-advanced is presented in detail. First, the scope of the AI for CSI feedback enhancement in 5G-Advanced is presented and discussed. Then, the main challenges and open problems in the standardization of AI for CSI feedback enhancement, especially focusing on performance evaluation and the design of new protocols for AI-enabled CSI feedback, are identified and discussed. This article provides a guideline for the standardization study of AI-based CSI feedback enhancement.

引用

页码：169 / 176

页数：8

共 15 条

[1]

3GPP, 2022, Tech. Rep.

[2]

[Anonymous], 2022, Standard 3GPP TR 21.917

[3]

[Anonymous], 2020, 3rd Generation Partnership Project (3GPP) TS 38.214

[4] Deep Learning-Based Implicit CSI Feedback in Massive MIMO [J].