Research Seminar

February 22, 2024

Location: SB 158

Time: 12:30 pm

Presenter: Aladdin Sleem

Artificial Intelligence Empowered Open Radio
Access Network (O-RAN) For Beyond 5G (B5G) Wireless Mobile Networks

Abstract:

Since its first deployment decades ago, mobile phone networks have been architected based on vendor-specific solutions for the Radio Access Network (RAN) and other components of the network. This limited the ability of mobile service providers to integrate different segments of their deployed mobile network unless they were all made by the same vendor.
Recently, the Open Access Radio Network (O-RAN) initiative was launched aiming at moving away from the single-vendor model for the entire RAN solution. It breaks down the radio access network into functional components and specifies set of standards that equipment suppliers should follow to produce mobile network devices that are non-proprietary and can be integrated with devices from other vendors. The RAN Intelligent Controller (RIC), which is a component of the O-RAN architecture, is a software component that controls and optimizes the functions of the radio access network. The RIC enables the integration of third-party applications that can lead to improving customer quality experience while lowering the operating cost of mobile operators.
Machine learning (ML) techniques, particularly Deep Learning (DL), have been gaining considerable attention in managing and optimizing the operations of various O-RAN components including its RAN Intelligent Controller (RIC). Deep learning models can learn from historical data and use this knowledge to predict network events such as service interruption or quality of service degradation. This gives the service provider the opportunity to be proactive in minimizing the impact of these events on network users. Additionally, near-real time network optimization tasks, such as dynamic spectrum allocation, can also be adjusted based on real-time network conditions using trained DL models.
This presentation will provide an overview of the O-RAN architecture and its benefits. Additionally, it will highlight the fundamentals of Deep Learning models and how they can be integrated into the O-RAN architecture to make future wireless networks smarter and more efficient.

Aladdin M. Sleem, Ph. D. is an Associate Professor of Computer Science in the College of Science Engineering and Technology. He is an expert in internet protocols and multimedia networking. He served as interim Chair for the Department of Engineering, interim Dean for the College of Science, Engineering and Technology and interim Associate Provost and Associate Vice President for Academic Affairs at Texas Southern University.