Towards 6G Semantic Communication: Technologies, Applications, and Research Challenges

This study provides a comprehensive literature review of the idea of Semantic Communication in 6G networks, covering its basic ideas, supporting technologies, potential applications and issues. Traditional communication systems prioritize bit-level correctness, but SemCom aims to create a more efficient, context-aware and successful communication model by preserving the meaning of the information being communicated. In this study the ideas behind SemCom and the three-layer communication model are first considered. Details of the technical, semantic and effectiveness layers are then given. The enabling technologies for SemCom are then examined, including deep learning, reinforcement learning, AI-native networks, edge computing and digital twins. The benefits and future opportunities of SemCom in various application domains are assessed, including IoT, smart cities, autonomous systems, the metaverse, UAV networks, and healthcare. Finally, we explore and provide remedies for the main barriers to mainstream SemCom adoption, including security vulnerabilities, semantic code optimization, resource allocation, and standards deficiencies. By reviewing the latest advances in the current literature on how SemCom should be applied in 6G communication systems, this study aims to provide a thorough foundation for further research.