Research on Intelligent Development and Full Life Cycle Operation and Maintenance Management of High-Speed Rail Communication Network Resources

To address spectrum fragmentation and operational response delays in high-speed rail scenarios, this study proposes a three-dimensional resource development model and an AI (Artificial Intelligence)-driven full-lifecycle operations and maintenance framework. In terms of spectrum, this study innovatively constructs a dynamic spectrum pool aggregation mechanism, integrating discrete frequency bands through 5G-Advanced three-carrier aggregation (3CC) technology and combining it with dynamic spectrum sharing (DSS) to achieve flexible scheduling of public and private network resources. In terms of computing power, a heterogeneous architecture of edge intelligent computing boards is designed, employing collaborative processing of FPGAs (Field-Programmable Gate Arrays) and neural processing units (NPUs), enabling hierarchical service scheduling based on reinforcement learning. In terms of data, a spectrum-computing power-linked digital twin platform is established, integrating a three-dimensional electromagnetic propagation model with a fault knowledge graph to enable visual resource management and root-cause diagnosis. This framework significantly improves spectrum utilization and operational automation, reduces the cost of multi-standard equipment compatibility, and provides a standardized solution for 6G high-speed rail communications.