Implanting Intelligence in 5G Mobile Networks—A Practical Approach

Cities evolve smart
Networks weave intelligence
Slicing future’s path
Network slicing
Machine learning
Random forest
Neural network

Malik, S., Khan, M. A., Aadam, El-Sayed, H., Khan, J., & Ullah, O. (2022). “Implanting Intelligence in 5G Mobile Networks—A Practical Approach”. Electronics, 11(23), Article 23. 10.3390/electronics11233933


Sumbal Malik

United Arab Emirates University

Manzoor Ahmed Khan

United Arab Emirates University

United Arab Emirates University

Hesham El-Sayed

United Arab Emirates University

Jalal Khan

United Arab Emirates University

Obaid Ullah

United Arab Emirates University


November 2022



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.

Important figures

Figure 4: Big picture of Data-Driven Network Slice Prediction.


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  title = {Implanting {{Intelligence}} in {{5G Mobile Networks}}—{{A Practical Approach}}},
  author = {Malik, Sumbal and Khan, Manzoor Ahmed and Aadam and {El-Sayed}, Hesham and Khan, Jalal and Ullah, Obaid},
  year = {2022},
  journal = {Electronics},
  volume = {11},
  number = {23},
  pages = {3933},
  publisher = {{Multidisciplinary Digital Publishing Institute}},
  issn = {2079-9292},
  doi = {10.3390/electronics11233933},