A systematic review conducted by Prof. Ping Zhang, Dr. Yiming Liu, Yile Song, and Jiaxiang Zhang from the State Key Laboratory of Networking and Switching Technology at Beijing University of Posts and Telecommunications delves into the world of semantic information and semantic communications. The researchers summarize the progress made in this field and highlight the major challenges, key issues, and potential research directions for developing modern semantic communication. The goal of this study is to inspire further scientific and industrial advancements in semantic communications.
The rapid development of information and communication technology (ICT) has had a profound impact on modern society. From the first generation (1G) to the fifth generation (5G) of mobile communication systems, there have been significant advancements in capacity and technology. However, these advancements have primarily focused on expanding the physical dimension of information transmission, often reaching the limits of Shannon’s information theory.
To address this issue, Prof. Ping Zhang and his team propose modern semantic communications, which involve co-designing source compression and channel transmission to leverage the inherent redundancy in information. This approach compensates for transmission errors and enables end-to-end system-wide optimization.
The article provides a comprehensive survey of modern semantic communication theories and methods, with a detailed introduction to the research in this field. It covers the semantic base (Seb)-based semantic transmission framework and the concept of semantic communication-empowered intelligent and concise (Intellicise) networks.
The review introduces a new fundamental model of semantic information representation known as the Seb model. It further explores the Seb-based semantic transmission framework, covering semantic representation and encoding, semantic modulation, semantic knowledge base modeling, and semantic metrics. The potential applications of modern semantic communication technology, such as Intellicise networks, goal-oriented applications, and the metaverse are also discussed.
Intellicise networks focus on utilizing native intelligence and endogenous simplified architecture to optimize systems. By equipping network nodes with intelligence, the network itself can evolve into a native intelligent system, capable of self-evolution, self-optimization, and self-balance.
In this context, semantic communication proves to be instrumental in extracting and transmitting the meaning of information, making it a promising technology for Intellicise networks. Moreover, semantic communication holds great potential for various vertical fields, including intelligent healthcare, transportation, and factories.
The review concludes by highlighting the remaining challenges and open issues in semantic communication. It also explores potential research directions that can further advance the field of modern semantic communication theories and methods.
Semantic communication has emerged as one of the potential key technologies for the future 6G systems. By revolutionizing basic information theories and making significant breakthroughs in intelligence, information, communication, and network technologies, it aims to transform the current paradigm of communication systems.