Semantic communication has shown great potential in boosting the effectiveness and reliability of communications. However, its systems to date are mostly enabled by deep learning, which requires demanding computing resources. This article proposes a framework for the computing networks enabled semantic communication system, aiming to offer sufficient computing resources for semantic processing and transmission. Key techniques including semantic sampling and reconstruction, semantic-channel coding, semantic-aware resource allocation and optimization are introduced based on the cloud-edge-end computing coordination. Two use cases are demonstrated to show advantages of the proposed framework. The article concludes with several future research directions.

翻译：语义通信在提升通信有效性和可靠性方面展现出巨大潜力。然而，目前大多数语义通信系统依赖深度学习实现，需要大量计算资源支持。本文提出一种基于计算网络的语义通信系统框架，旨在为语义处理与传输提供充足的计算资源。基于云边端计算协同，介绍了语义采样与重建、语义信道编码、语义感知资源分配与优化等关键技术。通过两个应用案例展示了所提出框架的优势。最后，本文展望了若干未来研究方向。