Existing communication systems are mainly built based on Shannon's information theory which deliberately ignores the semantic aspects of communication. The recent iteration of wireless technology, the so-called 5G and beyond, promises to support a plethora of services enabled by carefully tailored network capabilities based on the contents, requirements, as well as semantics. This sparkled significant interest in the semantic communication, a novel paradigm that involves the meaning of message into the communication. In this article, we first review the classic semantic communication framework and then summarize key challenges that hinder its popularity. We observe that some semantic communication processes such as semantic detection, knowledge modeling, and coordination, can be resource-consuming and inefficient, especially for the communication between a single source and a destination. We therefore propose a novel architecture based on federated edge intelligence for supporting resource-efficient semantic-aware networking. Our architecture allows each user to offload the computationally intensive semantic encoding and decoding tasks to the edge servers and protect its proprietary model-related information by coordinating via intermediate results. Our simulation result shows that the proposed architecture can reduce the resource consumption and significantly improve the communication efficiency.
翻译:现有的通信系统主要基于香农的信息理论,该理论故意忽视通信的语义方面。最近无线技术的迭代,即所谓的5G及以后,承诺支持大量基于内容、要求和语义的精心定制的网络能力所促成的服务。这引起了对语义通信的极大兴趣,这是一种将信息含入通信含义的新范式。在本篇文章中,我们首先审查经典的语义通信框架,然后总结阻碍其受欢迎的关键挑战。我们观察到,一些语义通信程序,例如语义检测、知识建模和协调,可能耗资不菲,效率低下,特别是用于单一来源和目的地之间的通信。因此,我们提出了一个基于美化边际智能的新结构,以支持资源高效的语义-语义网络。我们的架构允许每个用户从计算密集的语义编码和解码任务上卸载到边缘服务器,并通过中期结果协调保护其与模式相关的专有信息。我们的模拟结果表明,拟议的结构可以减少资源消耗量,大大改进通信效率。