Semantic-Enabled Video Transmission over Packet Erasure Channel

Packet loss is a critical issue in real-time video transmission systems. While video semantic communication with joint source-channel coding designs has demonstrated high performance in wireless channels at the physical layer, strategies for mitigating the effects of packet loss at higher layers have not been well studied. It is difficult to localize lost semantic features under packet loss scenarios, as semantic features need to be converted into bitstreams and then encapsulated into packets. In this paper, we propose a semantic-enabled video encoder that creates mappings between semantic information and data packets, leveraging the Packet Erasure Channel (PEC) to simulate packet loss conditions. Additionally, we design a semantic-enabled video decoder that improves information recovery in poor channel conditions. Furthermore, a semantic quality optimizer is placed at the receiver to enhance the adaptability of the real-time video transmission system under time-varying PEC. Experimental results show that the proposed scheme offers superior robustness against packet loss scenarios compared to conventional and AI-based benchmarks.