5 papers
Tokenized Joint Source-Network Coding for Loss-Resilient Video Streaming
Ke Yang, Sixian Wang, Kailin Tan +4
For decades, conventional video streaming systems have relied on packet-level forward error correction (FEC) codes and retransmissions to ensure reliable video delivery. However, i…
Loss-Resilient Semantic Communication over Packet-Loss Networks at Extreme-Low Bandwidth
Shengshi Yao, Jincheng Dai, Sixian Wang +5
In extreme-low bandwidth network scenarios, generative semantic codecs have emerged as promising solutions to reduce bandwidth cost for visual communications. However, these learne…
DiT-JSCC: Rethinking Deep JSCC with Diffusion Transformers and Semantic Representations
Kailin Tan, Jincheng Dai, Sixian Wang +5
Generative joint source-channel coding (GJSCC) has emerged as a new Deep JSCC paradigm for achieving high-fidelity and robust image transmission under extreme wireless channel cond…
Error-Resilient Semantic Communication for Speech Transmission over Packet-Loss Networks
Zhuohang Han, Jincheng Dai, Shengshi Yao +5
Real-time speech communication over wireless networks remains challenging, as conventional channel protection mechanisms cannot effectively counter packet loss under stringent band…
Generative AI Meets 6G and Beyond: Diffusion Models for Semantic Communications
Hai-Long Qin, Jincheng Dai, Guo Lu +6
Semantic communications mark a paradigm shift from bit-accurate transmission toward meaning-centric communication, essential as wireless systems approach theoretical capacity limit…