Resource Management Using Deep Reinforcement Learning for 5G and Beyond Wireless Networks:

I am pleased to share that we have recently presented a tutorial at the IEEE Wireless Communications and Networking Conference (WCNC) 2023, held in Glasgow, Scotland. The conference is a renowned annual event in the wireless research field, gathering together researchers, academics, industry professionals, and government officials.

Our tutorial, titled “Resource Management Using Deep Reinforcement Learning for 5G and Beyond Wireless Networks,” focused on the challenges of designing and deploying large-scale and heterogeneous networks. We collaborated with Dr. Ala Al-Fuqaha and my postdoc supervisor Dr. Mohamed Abdallah from Hamad Bin Khalifa University (HBKU), and Dr. Abdulmalik Alwarafy to deliver this tutorial.

During the presentation, we discussed the potential of deep reinforcement learning (DRL) for radio resource management (RRM) in future wireless HetNets. We explored the limitations of conventional RRM methods, highlighted the most widely used DRL algorithms, and provided examples of their effectiveness. Additionally, we delved into open challenges and future research directions in the context of DRL-based RRM.

As a researcher who is passionate about wireless communications, I found it an honor to share my knowledge with such a distinguished audience. It was also a valuable opportunity to learn from experts in the field and engage in discussions about cutting-edge research in wireless networking.