Text-Guided Token Communication for Wireless Image Transmission
Journal:
arXiv
Published Date:
Jul 8, 2025
Abstract
With the emergence of 6G networks and proliferation of visual applications,
efficient image transmission under adverse channel conditions is critical. We
present a text-guided token communication system leveraging pre-trained
foundation models for wireless image transmission with low bandwidth. Our
approach converts images to discrete tokens, applies 5G NR polar coding, and
employs text-guided token prediction for reconstruction. Evaluations on
ImageNet show our method outperforms Deep Source Channel Coding with Attention
Modules (ADJSCC) in perceptual quality and semantic preservation at
Signal-to-Noise Ratios (SNRs) above 0 dB while mitigating the cliff effect at
lower SNRs. Our system requires no scenario-specific retraining and exhibits
superior cross-dataset generalization, establishing a new paradigm for
efficient image transmission aligned with human perceptual priorities.
