6G Enabled Generative AI Services for Secure High-Speed Railway Networks

Running trains at higher speeds is a crucial trend in railway development. For future ultra-high-speed scenarios, the sixth-generation mobile communication technology (6G) can provide reliable transmission and enable generative artificial intelligence (GAI) services for secure high-speed railway networks. In this paper, we propose a 6G-enabled GAI service architecture for railway networks to enhance train operation safety. This architecture leverages integrated air-ground-train transmission, unmanned aerial vehicle (UAV), and distributed learning mechanisms to facilitate training and inference of GAI services. By analyzing the massive real-time data of critical equipment and areas with GAI techniques, early warnings and customized guidance for equipment breakdowns and natural disasters can be provided. Specifically, we propose integrating time-sensitive networking into 6G and jointly allocating time-spectrum resources in the air-ground-train integrated transmission to guarantee deterministic end-to-end latency in heterogeneous networks. Secondly, we develop a self-organization mechanism for a UAV cluster to perform various functions. The cluster comprises different types of UAVs and multiple intelligent algorithms are utilized during the self-organization process. Furthermore, a federated learning-based distributed training and inference framework for GAI services is studied, and several parallel computing techniques are proposed to reduce communication overhead. Simulation results demonstrate that learning-based resource allocation promotes the timeliness of model inference. Open research issues on further improving the performance of GAI services are also studied.