Semantic Knowledge Base Empowered Generative Semantic Communication
Shuling Li, Yaping Sun, Jinbei Zhang, Kechao Cai, Shuguang Robert Cui, Xiaodong Xu · IEEE Transactions on Communications · 2025
Semantic communication has drawn substantial attention as a promising paradigm to achieve effective and intelligent communications. However, efficient image semantic communication encounters challenges with a lower testing compression ratio (CR) and signal-to-noise ratio (SNR) compared to the training phase. To tackle this issue, we propose an innovative semantic knowledge base (SKB)-enabled generative semantic communication system for image classification task and image generation task. Specifically, a lightweight SKB, comprising class-level information, is exploited to guide the semantic communication process, which enables us to transmit only the relevant indices. This approach promotes the completion of the image classification task at the transmitter and significantly reduces the transmission load. Meanwhile, the class-level knowledge in the SKB facilitates the image generation task by allowing controllable generation, making it possible to generate class-consistent images in resource-constrained and low SNR scenarios. Furthermore, an adaptive CR and mode selection mechanism is designed to automatically adjust the CR and task mode, which allows the proposed system accommodate various CR and SNR conditions. Evaluation results indicate that the proposed method outperforms the benchmarks and achieves superior performance with minimal CR and SNR.