Generative artificial intelligence (GenAI) is a powerful technology that can leverage advanced AI algorithms to automatically create, manipulate, and modify valuable while diverse data. GenAI has recently attracted phenomenal attentions and can serve as a key supplement for empowering the other techniques, e.g., the emerging human digital twin (HDT) that requires high-fidelity virtual modeling and strong information interactions but possibly with scarce, biased and noisy data. This survey focuses on the implementation of GenAI enabled HDT over mobile networks, i.e., mobile GenAI-driven HDT, that particularly addresses human-centric applications, demanding customized service, user-friendly experience, context-aware response and seamless integration, while suffering from uncertain user mobility, time-varying internal/external factors, unstable end-to-end network performance, etc. We begin by elaborating the core requirements of human-centric applications, and then envision the potential of utilizing mobile GenAI-driven HDT. Following this, we delve into the fundamentals of mobile GenAI-driven HDT by discussing both GenAI and HDT in detail, and exploring how GenAI-driven HDT can be implemented under the end-edge-cloud collaborative framework over mobile networks. After that, we introduce several typical human-centric applications that may be well supported by mobile GenAI-driven HDT, including healthcare, manufacturing and intelligent transportation. Moreover, we analyze and review in-depth the technical issues and promising solutions for the realization of mobile GenAI-driven HDT, focusing on the large model deployment, personalized model evolution and immersive interactions over mobile networks. Finally, we conclude this survey by highlighting some open issues and future research directions.
