A Dynamic Adaptation Mechanism of Network Resource Based on Fuzzy Q-learning in High-speed Mobile Environment

The train-ground communication system in this paper realized the information interaction between the equipment on the train and the ground through continuous, bi-directional, and large-capacity communication. While ensuring the accurate closed-loop control of the train, it also provided entertainment business services for high-speed rail passengers. Due to the limited resources of the railway private network, this paper used public network resources to achieve the integration of emergency communications services and ordinary communications services. Aiming at the communication problems caused by the rapidly changing communication environment and the coexistence of heterogeneous networks in public network resources, a layered architecture of intelligent collaborative identification networks was proposed. At the same time, this paper proposed a dynamic adaptive algorithm for network resources based on fuzzy logic Q-learning, which was used for emergency communication services to issue resource scheduling policies under a new network architecture. Finally, simulation experiments verify the superiority of the adaptive resource scheduling algorithm in system communication performance.