Implanting Intelligence in 5G Mobile Networks—A Practical Approach

• DOI: 10.3390/electronics11233933
• Publication Date: 2022-11-28T12:38:49Z
• Authors: Sumbal Malik; Manzoor Ahmed Khan; Aadam; Hesham El-Sayed; Jalal Khan; Obaid Ullah
• Keywords: 11. Sustainability; 0202 electrical engineering, electronic engineering, information engineering; 5G; network slicing; machine learning; random forest; neural network; 02 engineering and technology

With the advancement in various technological fronts, we are expecting the design goals of smart cities to be realized earlier than expected. Undoubtedly, communication networks play the crucial role of backbone to all the verticals of smart cities, which is why we are surrounded by terminologies such as the Internet of Things, the Internet of Vehicles, the Internet of Medical Things, etc. In this paper, we focus on implanting intelligence in 5G and beyond mobile networks. In this connection, we design and develop a novel data-driven predictive model which may serve as an intelligent slicing framework for different verticals of smart cities. The proposed model is trained on different machine learning algorithms to predict the optimal network slice for a requested service resultantly assisting in allocating enough resources to the slice based on the traffic prediction.