Transformer-based Channel Prediction for Rate-Splitting Multiple Access-enabled Vehicle-to-Everything Communication

Shengyu Zhang1; Shiyao Zhang2; Yijie Mao3; Lawrence K. Yeung4; Bruno Clerckx5; Tony Q.S. Quek1

2024

10.1109/TWC.2024.3395670

IEEE Transactions on Wireless Communications   影响因子和分区

1558-2248

Channel Prediction Channel State Information (CSI) Transformer Rate-Splitting Multiple Access (RSMA)

EI

其他

COMPUTER SCIENCE

IEEE

1.Information Systems Technology and Design Pillar, Singapore University of Technology and Design, Singapore
2.Research Institute for Trustworthy Autonomous Systems, Southern University of Science and Technology, Shenzhen, China
3.School of Information Science and Technology, ShanghaiTech University, Shanghai, China
4.Department of Electrical and Electronic Engineering, The University of Hong Kong, HKSAR, China
5.Department of Electrical and Electronic Engineering, Imperial College London, London, U.K.

Shengyu Zhang,Shiyao Zhang,Yijie Mao,et al. Transformer-based Channel Prediction for Rate-Splitting Multiple Access-enabled Vehicle-to-Everything Communication[J]. IEEE Transactions on Wireless Communications,2024,PP(99):1-1.

Shengyu Zhang,Shiyao Zhang,Yijie Mao,Lawrence K. Yeung,Bruno Clerckx,&Tony Q.S. Quek.(2024).Transformer-based Channel Prediction for Rate-Splitting Multiple Access-enabled Vehicle-to-Everything Communication.IEEE Transactions on Wireless Communications,PP(99),1-1.

Shengyu Zhang,et al."Transformer-based Channel Prediction for Rate-Splitting Multiple Access-enabled Vehicle-to-Everything Communication".IEEE Transactions on Wireless Communications PP.99(2024):1-1.