Abstract
China has entered a new fifth-generation (5G) technological period, college students are relatively fast to absorb new things, and conventional teaching methods are incapable of properly stimulating students' interest in sporting activities. As a result, the 5G integrated teaching paradigm, which is based on communication technology, is an unavoidable reform of sports remote education. For a long time, technology and sports have been inextricably linked. However, new possibilities on the Internet are fast developing, resulting in massive volumes of data. In this paper, we propose a novel 5G framework for efficient sports distance education. Initially, the sports dataset is preprocessed using normalization, and the features are extracted using Principal Component Analysis (PCA). Following feature selection, a Hierarchical Multiscale Convolutional Neural Network (HM-CNN) is used to categorize and initialize the 5G utilizing the Enhanced Transfer Control Protocol (E-TCP) for efficient data transmission. The Elevated Ant Colony Optimization Algorithm improves the performance of the suggested system even more (EACO). The experimental results indicate that 5G integrated education reform based on communication technology may successfully enhance the number of college students' sports population.
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