Semantic Communication
Semantic communication aims to transmit only the essential meaning of data, rather than raw bits, improving efficiency and bandwidth utilization. Current research focuses on integrating generative AI models, such as diffusion models and transformers, with techniques like federated learning and joint source-channel coding to achieve robust and efficient semantic encoding and decoding across various modalities (images, speech, video). This approach holds significant promise for enhancing communication in resource-constrained environments and enabling new applications in areas like autonomous driving, IoT, and satellite networks by prioritizing meaningful information and reducing transmission overhead.
Papers
Deep Image Semantic Communication Model for Artificial Intelligent Internet of Things
Li Ping Qian, Yi Zhang, Sikai Lyu, Huijie Zhu, Yuan Wu, Xuemin Sherman Shen, Xiaoniu Yang
Deep Learning-Empowered Semantic Communication Systems with a Shared Knowledge Base
Peng Yi, Yang Cao, Xin Kang, Ying-Chang Liang