NSF-MeitY: NeTS: Small: Towards Learning Enabled Sustainable Service Handling in 6G

This is a collaborative project between universities in the United States and India to enable sustainable next generation cellular wireless (6G) services. Traditional approaches to resource allocation in wireless communications networks are based on mathematical models with known parameters. However, such models, along with the complete knowledge of the parameters, are unlikely to be available in 6G systems. An online learning paradigm capable of adapting to evolving and uncertain situations will prove invaluable in this scenario. The project develops learning-based control strategies for sustainable network operations with enhanced energy efficiency and improved resource usage in future mobile networks. The project also includes an innovative education plan contributing to workforce development from K-12 students to STEM and an innovative workforce development and training plan through short-term training programs for students and industry/working professionals. The proposed research comprises three comprehensive thrusts and an evaluation plan. Thrust 1 focuses on creating a learning-based framework for resource allocation in the core network. Thrust 2 focuses on developing real-time resource allocation strategies for improving energy efficiency and sustainability in Radio Access Networks (RAN), with support for massive connectivity. Thrust 3 includes the development of an adaptive security mechanism for the 6G network. The algorithms developed in the project are implemented and evaluated on ns3-ai software integrated with learning capabilities, and a simulator and a testbed available at IIT Bombay. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.