5 papers
Federated Learning Enhanced by Feature Reconstruction for Semantic Communication Module Updates of Agents
Yoon Huh, Bumjun Kim, Wan Choi
Recent advancements in semantic communication have primarily focused on image transmission, where neural network-based joint source-channel coding modules play a central role. Howe…
Markov-Enforced Discrete Diffusion Model for Digital Semantic Symbol Error Correction
Yoon Huh, Jeongho Kang, Wan Choi
Diffusion models (DMs) have achieved remarkable success across various domains owing to their strong generative and denoising capabilities. Meanwhile, semantic communication based…
Extended Universal Joint Source-Channel Coding for Digital Semantic Communications: Improving Channel-Adaptability
Eunsoo Kim, Yoon Huh, Wan Choi
Recent advances in deep learning (DL)-based joint source-channel coding (JSCC) have enabled efficient semantic communication in dynamic wireless environments. Among these approache…
Feature Reconstruction Aided Federated Learning for Image Semantic Communication
Yoon Huh, Bumjun Kim, Wan Choi
Research in semantic communication has garnered considerable attention, particularly in the area of image transmission, where joint source-channel coding (JSCC)-based neural networ…
Universal Joint Source-Channel Coding for Modulation-Agnostic Semantic Communication
Yoon Huh, Hyowoon Seo, Wan Choi
From the perspective of joint source-channel coding (JSCC), there has been significant research on utilizing semantic communication, which inherently possesses analog characteristi…