Generative artificial intelligence (GAI) has emerged as a rapidly burgeoning field demonstrating significant potential in creating diverse contents intelligently and automatically. To support such artificial intelligence-generated content (AIGC) services, future communication systems should fulfill much more stringent requirements (including data rate, throughput, latency, etc.) with limited yet precious spectrum resources. To tackle this challenge, semantic communication (SemCom), dramatically reducing resource consumption via extracting and transmitting semantics, has been deemed as a revolutionary communication scheme. The advanced GAI algorithms facilitate SemCom on sophisticated intelligence for model training, knowledge base construction and channel adaption. Furthermore, GAI algorithms also play an important role in the management of SemCom networks. In this survey, we first overview the basics of GAI and SemCom as well as the synergies of the two technologies. Especially, the GAI-driven SemCom framework is presented, where many GAI models for information creation, SemCom-enabled information transmission and information effectiveness for AIGC are discussed separately. We then delve into the GAI-driven SemCom network management involving with novel management layers, knowledge management, and resource allocation. Finally, we envision several promising use cases, i.e., autonomous driving, smart city, and the Metaverse for a more comprehensive exploration.
GenED-SC: Generative Editing Semantic Communication with Integrated Multi-Modal LLMs
College of Electronics and Information Engineering, Shenzhen University（深圳大学电子与信息工程学院）；School of Ocean Engineering and Technology, Sun Yat-sen University（中山大学海洋工程与技术学院）；Department of Electrical and Software Engineering, University of Calgary（卡尔加里大学电气与软件工程系）
Training-Free Multi-User Generative Semantic Communications via Null-Space Diffusion Sampling
Dept. of Information Engineering, Electronics, and Telecommunications of Sapienza University of Rome（罗马大学信息工程、电子与电信系）；School of Electrical and Mechanical Engineering, The University of Adelaide（阿德莱德大学电气与机械工程学院）；ISTD Pillar, Singapore University of Technology and Design（新加坡科技设计大学ISTD支柱）
Generative AI Meets 6G and Beyond: Diffusion Models for Semantic Communications
Beijing University of Posts and Telecommunications（北京邮电大学）；Shanghai Jiao Tong University（上海交通大学）；East China Normal University（华东师范大学）；Tsinghua University（清华大学）；Hong Kong University of Science and Technology（香港科技大学）
Generative Video Semantic Communication via Multimodal Semantic Fusion with Large Model
School of Information and Electronics, Beijing Institute of Technology（信息与电子学院，北京理工大学）；School of Computer Science and Engineering, Nanyang Technological University（计算机科学与工程学院，南洋理工大学）
