摘要：The development of the Internet of Things (IoT) made it possible for technology to communicate physical education by connecting cost-effective heterogeneous devices and digital applications to uncontrolled and accessible environments. This study explores the reforms and development of college physical education teaching services under the background of the 5th Generation Mobile Communication Technology. The data channel algorithm and the Internet of things (IoT) resource allocation algorithm for deep reinforcement learning are adopted to analyze the physical education reform in colleges. The application scenario of the IoT, the Multiple Input Multiple Output (MIMO) precoding technology, and the repeated lifting coverage of transmission time interval (TTI) in data transmission are examined based on the downlink system of the Un-narrow Band Internet of Things (U-NB-IoT). Moreover, the resource allocation problem under the access of massive IoT devices is solved through the deep reinforcement learning framework. Results show that quality of service is difficult to measure the communication network centered on the integration of teachers and students, while the quality of experience can make teachers and students feel satisfied. Moreover, quality of experience can measure the quality of service by the satisfaction of teachers and students to experience teaching resources. The resource allocation algorithm proposed can improve the experience of teachers and students using teaching resources, make the satisfaction of teachers and students reach the ideal value, further optimize the traditional problems existing in teaching, and improve the quality of students in all aspects.
