Announcement of Two New Grants Awarded From NSF

Grant 1

Collaborative Research: CISE Core Small: NeTS: Intelligent Reflecting Surface Assisted Physical Layer Security Enhancement for Ultra-dense IoT Networks

With billions of Internet of Things (IoT) devices supporting healthcare, transportation, and industrial systems, ensuring secure and efficient communication has become a major challenge. Conventional cryptographic methods are often too heavy for small, resource-limited IoT devices. This project takes a new approach by securing communication at the physical wireless layer, using the randomness of radio signals themselves. By integrating intelligent reflecting surfaces (IRS) — smart, energy-efficient panels that reconfigure how wireless signals propagate — the research will improve both security and energy efficiency in ultra-dense IoT networks. Beyond technical advances, this project will provide hands-on research opportunities for students across institutions, strengthen cybersecurity education, and contribute to workforce development in the U.S.

Funding Agency: National Science Foundation (NSF)

Award Number (FAIN): 2523751

Amount: $225,000 (SFSU portion)

Period of Performance: 10/01/2025 – 09/30/2028

Principal Investigator: Qun Wang (San Francisco State University)
 

Collaborators:

• Haijian Sun (University of Georgia)

• Hao Yue (University of California, Santa Cruz)

Grant 2

CRII: NeTS: Intelligent Reflecting Surface Assisted Transmitting and Sensing for Spectrum Sharing and Coexistence of Heterogeneous Wireless Systems

As wireless networks expand to support smart cities, autonomous vehicles, and industrial IoT, different systems such as mobile networks, Wi-Fi, and radar must all share the same limited spectrum. This creates interference and reliability challenges. This project develops new Transmitting and Sensing techniques to enable better coexistence of diverse wireless systems with spectrum sharing. By combining machine learning with physics-based design, the research aims to make spectrum use more efficient, fair, and energy-conscious. The results are expected to: 1. Improve connectivity and reduce interference in crowded wireless environments. 2. Train the next generation of engineers by integrating cutting-edge wireless and AI research into education. 3. Support national priorities for equitable and reliable access to wireless communication resources.

Funding Agency: National Science Foundation (NSF)

Award Number (FAIN): 2451262

Amount: $175,000

Period of Performance: 07/01/2025 – 06/30/2027

Principal Investigator: Qun Wang (San Francisco State University)