O-RAN Compliant RAN Resource Management for Next-generation Mobile and C-V2X
Southwest Virginia Node
Vijay Shah, research assistant professor, electrical and computer engineering, Virginia Tech
Bo Yu, post-doctoral associate, computer science, George Mason University; Ying Wang, CCI 5G Testbed radio frequency engineer
The future generation mobile network is expected to support various types of services such as eMBB (enhanced Mobile Broadband), mMTC (massive Machine Type Communications), and URLLC (Ultra-Reliable and Low Latency Communications) and beyond, while at the same time fulfilling different QoS/QoE requirements. These requirements will be determined between the network operator and end-users (human users, autonomous vehicles etc.) with specifications of key performance indicators (KPIs), such as throughput, latency, connectivity, etc. As a service-based architecture, network slicing enables a diverse range of services to be accommodated in the same physical radio access network (RAN). To satisfy service requirements, the key is the placement of distributed RAN resources (e.g, spectrum, computation, memory resources etc.) that support dynamic customization of each slice. In this proposal, we envision to architect an O-RAN complaint user-driven RAN resource management (RRM) system that dynamically predicts network progression and conducts network design (i.e., RAN resource management) strategies and auto-deployment within the network periodically through temporal data mining of the user traffic and mobility behaviors, with a focus on two usecases: human users in 5G network and vehicles in C-V2X scenarios. Our specific tasks are: (i) prototying intelligent user-driven RRM system, (ii) Adapting user-driven RRM system to C-V2X, (iii) ensuring O-RAN compliance design and testing of user driven RRM system, and finally, (iv) Integration and evaluation of user driven RRM system using CCI 5G testbed.