2022/10/27 by Haotian Wu, Wu, Haotian, Yulin Shao +7 · 2 citations
Computer Science · Engineering · #94A24 #Advanced Data Compression Techniques #Advanced MIMO Systems Optimization #Advanced Wireless Communication Technologies #E.4 #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Information Theory (cs.IT) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2210.15347
openalex publication_date 2022/10/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper presents a vision transformer (ViT) based joint source and channel coding (JSCC) scheme for wireless image transmission over multiple-input multiple-output (MIMO) systems, called ViT-MIMO. The proposed ViT-MIMO architecture, in addition to outperforming separation-based benchmarks, can flexibly adapt to different channel conditions without requiring retraining. Specifically, exploiting the self-attention mechanism of the ViT enables the proposed ViT-MIMO model to adaptively learn the feature mapping and power allocation based on the source image and channel conditions. Numerical experiments show that ViT-MIMO can significantly improve the transmission quality cross a large variety of scenarios, including varying channel conditions, making it an attractive solution for emerging semantic communication systems.