Project Grant 2225617

This three-year, $600,000 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program will support the development of next generation 6G wireless communication systems using machine learning algorithms. Specifically, the award to the University of California, San Diego will fund four components: machine learning-based sparse channel modeling in constrained environments; novel block-sparse channel modeling using domain knowledge and data-driven techniques; incorporation of reconfigurable intelligent surfaces for channel morphing; and experimental work including channel sounding and ray tracing to validate and refine theoretical models. The work aims to address challenges in deploying millimeter-wave and terahertz frequency bands for massive MIMO systems in 6G by developing non-traditional processing algorithms using machine learning networks to deal with nonlinearities from small form factors. Outcomes have the potential to help maintain U.S. leadership in wireless technology and train next-generation researchers.