2022/06/16 by Xiao Han, Zhiqin Wang, Xiao, Han +17
Computer Science · Engineering · #Antenna Design and Optimization #FOS: Electrical engineering #Signal Processing (eess.SP) #Speech and Audio Processing #Wireless Signal Modulation Classification #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2206.07949
openalex publication_date 2022/06/16 · openalex created_date 2022/06/19 · openalex updated_date 2026/07/28
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.