The 6G network covers the entire space, air, ground, and sea. For diversified and personalized scenarios, the 6G network needs to provide customized services, that is, on-demand services. In order to realize on-demand services in all domains and scenarios, accurate, real-time, and intelligent cognition of the characteristics of the scenarios is an important prerequisite. How to enable the network to autonomously and intelligently recognize different scenarios and services, convert them into scenario-specific network key performance indicator (KPI), and further efficiently schedule network resources is a key problem that urgently needs to be solved. This paper applies the knowledge graph to the cognitive recognition of network scenarios, forms a standardized description of 6G network scenarios, and builds a knowledge graph based on the 6G scenario ontology. At the same time, a scene cognition reasoning method based on knowledge graph embedding is proposed, which realizes the embedding learning of graph nodes and relationships and reasons about scene feature nodes, achieving high accuracy. The method proposed in this paper helps to realize the autonomous control of the service life cycle of scene awareness, cognition, and on-demand services in the 6G full-scenario network, and has important innovation and guiding significance for improving the autonomy and intelligence of the next-generation network.