Investigating Machine Learning Techniques in Performance Improvement for the Next Generation Wireless Networks

The new generation 5G wireless networks will have a huge impact on the society due to the high bandwidth and capacities they provide. The traffic volume is expected to grow significantly and new varieties of applications, e.g., Internet of Things and vehicular networking, are anticipated. As a result, effective management of the new networks will become much more complicated and challenging. Machine learning techniques have made unprecedented progress in recent years, as they are highly efficient for data-driven applications. The proposed project is to investigate machine learning techniques and apply them to 5G networks to effectively facilitate network management.

Faculty Supervisor:

Chung-Horng Lung;Samuel Ajila


Calvin Jary;Gazoan Ahmed


Ericsson Canada


Engineering - computer / electrical



Carleton University



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