This $700,000 Project Grant award, funded by the National Science Foundation (NSF) Division of Computer and Network Systems under the CFDA 47.070 Computer and Information Science and Engineering program, supports research to enable intelligent, real-time control and optimization of next-generation cellular wireless networks. The Texas A&M Engineering Experiment Station (Tees), a division of the Texas A&M University System, is leading this collaborative research effort. The project aims...
This $400,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) is for a 3-year research project led by North Carolina State University (NC State). The project aims to develop robust intelligent algorithms for managing and optimizing dynamic wireless spectrum access, which is critical for emerging technologies like autonomous vehicles and the metaverse. Key innovations include techniques for...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award for $500,000 to Arizona State University provides funding to develop novel mathematical frameworks, techniques, and architectures for distributed multi-modal sensing-aided large-scale MIMO and high-frequency communication networks. The goal is to enable scalable and reliable next-generation wireless networks to support emerging applications in autonomous...
This Project Grant award of $550,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development and validation of a distributed, data-driven architecture for dynamic spectrum management among heterogeneous wireless systems. The goal is to overcome the limitations of centralized spectrum management and increase spectrum efficiency. The project focuses on designing protocols and algorithms for a Distributed...
The National Science Foundation (NSF) awarded a $300,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to North Carolina State University (NC State) to study the integration of aerial network elements (ANEs) such as drones and unmanned aerial vehicles into existing terrestrial wireless networks. The 3-year project, titled "NETS: SMALL: COLLABORATIVE RESEARCH: NSF-NSERC: 3D HARMONY: ARTIFICIAL INTELLIGENCE ENABLED HARMONIOUS WIRELESS...
Texas Tech University received a two-year, $293,229 project grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA #47.070) to support research titled "COLLABORATIVE RESEARCH: CNS CORE: SMALL: FUNDAMENTALS OF ULTRA-DENSE WIRELESS NETWORKS WITH GENERALIZED REPULSION" from October 1, 2021 through September 30, 2023. The Computer and Information Science and Engineering program supports investigator-initiated research and education...
This $305,746 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop technical solutions for a more open and democratized wireless access ecosystem. The project, titled "COLLABORATIVE RESEARCH: NETS: SMALL: LAST MILE AS A FREE MARKET: DEMOCRATIZING WIRELESS ACCESS WITH ON-DEMAND DECENTRALIZED CONTRACTS," is led by North Carolina State University. The key objectives are to: 1)...
The National Science Foundation (NSF) awarded a $600,000 Computer and Information Science and Engineering (CFDA 47.070) Project Grant to the University of California, Irvine (UC Irvine) to conduct research on asynchrony and limited feedback in next-generation wireless communications systems. The 3-year project aims to analyze the performance and design of multiple access techniques, such as non-orthogonal and grant-free systems, that allow for simultaneous transmission by multiple users while...
The National Science Foundation (NSF) awarded a 3-year, $300,000 Project Grant to the University of California Irvine (UC Irvine) under the Computer and Information Science and Engineering (CFDA 47.070) program. The purpose of this collaborative research award is to develop advanced signal processing and resource allocation methods for cell-free massive multiple-input multiple-output (MIMO) wireless access networks, which can provide more uniform coverage and data rates compared to traditional...
This National Science Foundation Project Grant award of $279,999 provides funding from Fiscal Year 2023 to 2026 under the federal Computer and Information Science and Engineering program (CFDA 47.070) to the University of Massachusetts Amherst. The award will support research activities to develop a cross-system architecture design for autonomous wireless networks based on lifelong machine learning. Specifically, the University of Massachusetts Amherst will conduct research to advance the design...
This $557,659 National Science Foundation (NSF) Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program aims to develop a comprehensive theory for second-order cross-layer design of wireless networks. The project, awarded to the Texas A&M Engineering Experiment Station (Tees), seeks to advance the fundamental understanding of wireless network capabilities in supporting emerging applications like virtual reality and connected vehicles. The key objectives are to unify the analysis and optimization of diverse performance metrics, facilitate the development of next-generation network algorithms, and tightly integrate research with education and outreach initiatives. The project pursues three complementary research thrusts: characterizing the second-order capacity region and resource allocation for centrally scheduled wireless networks, developing distributed policies to address interference, and tailoring network policies for diverse application requirements. This work is expected to advance the theoretical foundations of wireless networking and enable practical implementation of novel network algorithms to support future wireless technologies.