Optimally Bridging Semantics and Data: Generative Semantic Communication via Schrödinger Bridge
Generative Semantic Communication (GSC) is a promising solution for image transmission over narrow-band and high-noise channels. However, existing GSC methods rely on long, indirect transport trajectories from a Gaussian to an image distribution guided by semantics, causing severe hallucination and high computational cost. To address this, we propose a general framework named Schrödinger Bridge-based GSC (SBGSC). By leveraging the Schrödinger Bridge (SB) to construct optimal transport trajectories between arbitrary distributions, SBGSC breaks Gaussian limitations and enables direct generative decoding from semantics to images. Within this framework, we design Diffusion SB-based GSC (DSBGS...
| Authors | Dahua Gao, Ruichao Liu, Minxi Yang et al. |
|---|---|
| Primary category | eess.IV |
| Published | 20 April 2026 |
| Last updated at source | 20 April 2026 |
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