A Survey of Optimal Resource Allocation in Semantic Communications: Technologies, Development Trends, and Applications

As an emerging communication paradigm, semantic communications (SC) focuses on the semantic content of information transmission, aiming to achieve more efficient and accurate information interaction. However, SC requires an in-depth analysis of information semantics and accurate adaptation to application scenarios. With the substantial growth in information volume, richness, and application diversity, the resources, constraints, and requirements associated with SC systems have also increased. Optimal resource allocation (ORA) of SC can effectively deal with these practical problems, a key technology for improving communication efficiency. In complex network environments and special scenarios, communication resources are limited. Increasing transmission efficiency, ensuring accuracy and quality of information, and reducing energy consumption can be achieved by rationally allocating bandwidth, power, and related resources. Since SC technology is still in its early stages of development, there is a lack of a comprehensive review of ORA for SC in the existing literature. This paper provides a comprehensive review of ORA for SC. First, the basic concepts, characteristics and development motivations for SC and ORA are reviewed. Then, a comprehensive analysis of the key technologies for ORA in SC is presented, covering end-to-end and semantic network multi-link ORA. These technologies include technology for predicting resource demand based on semantic understanding, resource optimization technology for semantic information (SI) processing and transmission, and technology for dynamic resource adjustment. Then, a conceptual ORA framework is synthesized from the reviewed technologies to unify key design principles and provide a foundation for future research. In addition, this paper provides research prospects in future trends of ORA for SC, comprising emerging artificial intelligence (AI) and machine learning, laying the foundation for next-generation intelligent communication networks. Finally, this paper points out the main application direction of ORA in SC, which reflects the practical significance of this study.