This three-year, $1,199,824 project grant from the National Science Foundation's Division of Computing and Communication Foundations, under the Computer and Information Science and Engineering program (CFDA #47.070), will support the development of a "RADIORTML" platform at Northeastern University. RADIORTML aims to demonstrate the feasibility of automatically optimizing radio frequency integrated circuits in real-time through machine learning techniques implemented directly on reconfigurable hardware. Novel deep reinforcement learning algorithms will be created to provide unprecedented flexibility while improving energy efficiency and minimizing interference for wireless receivers. This will transform how radio frequency system optimization is done by showing real-time machine learning-based adaptation of parameters can significantly improve performance. Outcomes seek to benefit the design and optimization of low-power radio frequency circuits for adaptive, energy-efficient communication.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $599.9k | 6/30/22 |