This $450,000 Project Grant was awarded by the National Science Foundation's (NSF) Engineering program (CFDA 47.041) to the Texas A&M Engineering Experiment Station (Tees) to conduct research on joint source-channel coding using machine learning techniques for communication systems. The key objectives are to improve the understanding of the underlying mechanisms of machine learning-based solutions, with the goal of developing computationally efficient, robust, and flexible designs for future communication networks. The research plan includes studying signal representations and neural network interfaces, understanding performance gains and degradation mechanisms, investigating neural joint source-channel coding for feedback channels and multi-user settings, and exploring the use of generative models. Some of the developed schemes will be implemented on a software-radio testbed to demonstrate their effectiveness in computation-constrained environments. This collaborative project between Texas A&M University and Imperial College, London, will also provide opportunities for new curriculum development and study-abroad programs for undergraduate students. The award period is from May 1, 2025, to April 30, 2028.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $450.0k | 4/24/25 |