AI Enlightens Wireless Communication:A Transformer Backbone for CSI Feedback  

作　　者：Xiao Han Wang Zhiqin Li Dexin Tian Wenqiang Liu Xiaofeng Liu Wendong Jin Shi Shen Jia Zhang Zhi Yang Ning 

机构地区：[1]Dept.of Standards Research,OPPO,Beijing 100026,China [2]China Academy of Information and Communications Technology,Beijing 100191,China [3]National Mobile Communications Research Laboratory,Southeast University,Nanjing 211189,China

出　　处：《China Communications》2024年第12期243-256,共14页中国通信（英文版）

摘　　要：This paper is based on the background of the 2nd Wireless Communication Artificial Intelligence(AI)Competition(WAIC)which is hosted by IMT-2020(5G)Promotion Group 5G+AIWork Group,where the framework of the eigenvector-based channel state information(CSI)feedback problem is firstly provided.Then a basic Transformer backbone for CSI feedback referred to EVCsiNet-T is proposed.Moreover,a series of potential enhancements for deep learning based(DL-based)CSI feedback including i)data augmentation,ii)loss function design,iii)training strategy,and iv)model ensemble are introduced.The experimental results involving the comparison between EVCsiNet-T and traditional codebook methods over different channels are further provided,which show the advanced performance and a promising prospect of Transformer on DL-based CSI feedback problem.

关 键 词：CSI feedback deep learning MIMO TRANSFORMER 

分 类 号：TN929.5[电子电信—通信与信息系统] TP18[电子电信—信息与通信工程]