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SeoulTech’s ConcreteSC Advances Digital Semantic Communication With Codebook-Free Quantization

The end-to-end trainable method replaces bulky codebooks with temperature-controlled concrete distributions to robustly digitize meaning under channel noise.

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Overview

  • The research, published June 19 in IEEE Wireless Communications Letters, is now being highlighted in late-August coverage by Tech Xplore, Tech Explorist, and EurekAlert!
  • Simulations on ImageNet under Rayleigh and Rician fading show consistent SSIM and PSNR gains over vector-quantization baselines.
  • ConcreteSC directly generates bitstreams through a fully differentiable quantizer that enables end-to-end training under noisy channels.
  • Computational complexity scales linearly with bit length, reducing overhead and allowing integration into existing semantic communication frameworks.
  • Reports cite up to roughly threefold improvements in image quality, with one outlet alone claiming a 39× processing speedup that has not been independently verified.