A Swin Transformer With Channel-Adaptive Modulation for Semantic Image Transmission Over MIMO Channels
Abstract
Semantic communication has advanced rapidly, yet most frameworks target SISO Gaussian or Rayleigh channels, limiting deployment in practical MIMO systems. We present MIST (MIMO and Modulation-aware Image Semantic Transmission), an end-to-end framework for image semantics over MIMO. MIST uses a Swin Transformer backbone, a channel-adaptive modulation module that leverages CSI and SNR to refine latent semantics, and an adaptive channel compression stage to enhance robustness to diverse channel conditions within one model. Extensive experiments under MIMO fading show consistent gains over conventional, CNN-based, and Transformer-based baselines across multiple image resolutions.
Fields of Study & Subjects
Wireless Signal Modulation Classification
Advanced Wireless Communication Technologies
Wireless Communication Security Techniques
Publication details
- Journal / source
- IEEE Communications Letters
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Volume
- 30
- Pages
- 892–896
- Publication date
- 1 January 2026