| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | August 23, 2019 |
| Latest Amendment Date: | July 18, 2023 |
| Award Number: | 1910853 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Murat Torlak
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | October 1, 2019 |
| End Date: | March 31, 2024 (Estimated) |
| Total Intended Award Amount: | $499,967.00 |
| Total Awarded Amount to Date: | $563,967.00 |
| Funds Obligated to Date: |
FY 2020 = $16,000.00 FY 2021 = $16,000.00 FY 2022 = $16,000.00 FY 2023 = $16,000.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
1600 HAMPTON ST COLUMBIA SC US 29208-3403 (803)777-7093 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
SC US 29208-0001 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
Special Projects - CNS, Networking Technology and Syst, EPSCoR Co-Funding |
| Primary Program Source: |
01002021DB NSF RESEARCH & RELATED ACTIVIT 01001920DB NSF RESEARCH & RELATED ACTIVIT 01002324DB NSF RESEARCH & RELATED ACTIVIT 01002223DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Millimeter-wave is a core technology for next-generation wireless and cellular networks (5G and beyond). Networks using millimeter-wave technologies are expected to satiate the rapidly growing customer appetite for mobile data and to meet the stringent throughput, latency, and reliability requirements of emerging applications, such as immersive virtual and mixed reality, tactile internet, vehicular communications, and autonomous vehicles safety. However, high directionality, high channel dynamics, and sensitivity to blockages render state-of-the-art millimeter-wave technologies unsuitable for low-latency, high performance, and ultra-reliable applications. This research project focuses on designing software-hardware reconfigurable systems to address the key challenges and improve the performance, availability, and reliability of mobile millimeter-wave networks. This project will impact the broader population positively because it yields near-term benefits in 5G infrastructure and paves the way for long-term millimeter-wave research. Furthermore, this project will engage in outreach activities and involve a diverse set of students, particularly, women and minorities, leveraging the experimental nature of the research on next-generation wireless and cellular networks.
The project addresses the key challenges by executing three thrusts: (1) MilliNet: To overcome high signal attenuation, millimeter-wave radios must focus their power via highly directional, electronically steerable beams. But, aligning the beams and maintaining the link between devices during obstruction and mobility are the fundamental barriers toward reliable connection. MilliNet, a faster beam alignment protocol, draws on ideas from the sparse channel recovery, allowing the radios to quickly discern the best physical millimeter-wave paths even under thousands of beams and picocell choices. (2) ReconMilli: To achieve spectrum flexibility, next-generation radios must be able to operate over a wide range of the spectrum, from micro-wave to millimeter-wave. But the fundamental challenge is that physical space on mobile devices is limited. ReconMilli, a reconfigurable antenna design, joins multiple millimeter-wave antennas physically into a micro-wave antenna, but splits it, when needed, into multiple millimeter-wave antennas; thus, achieving spectrum flexibility and saving physical space. (3) LiMesh: To make the deployment and maintenance of a 5G picocell mesh easy, mobile operators will use multi-Gbps fixed millimeter-wave links. Yet, disruptions in the wireless mesh are common; but, more importantly, such disruptions are catastrophic for ultra-reliable connectivity. LiMesh, an ultra-reliable picocell mesh design, leverages the fixed geometrical arrangement of the directional links to infer disruptions using a space-time failure correlation metric proactively. The research project will design, build, and empirically validate the proposed systems in millimeter-wave wireless test-beds.
This project is jointly funded by the Computer and Network Systems (CNS) division and the Established Program to Stimulate Competitive Research (EPSCoR).
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The NSF project aimed to develop a software-hardware reconfigurable approach to design efficient millimeter-wave networks and sensing applications. The intellectual merit of this project is reflected in the successful development and demonstration of three major reconfigurable systems, each showcasing significant performance gains and practical applications.
The first system centered on enhancing thermal efficiency and reliability in mobile 60 GHz networks. A measurement platform using Commercial-Off-The-Shelf 60 GHz picocells and smartphones was developed to characterize throughput and thermal performance. Key developments included a model for measuring the effects of throughput and data transfer parameters on thermal performance, an online estimation model for throughput vs. thermal profiles, and a heuristic mmWave multi-antenna coordination algorithm. The system demonstrated significant improvements, such as an upper bound of median peak temperature reduction by 12 degrees Celsius in static conditions and 9.5 degrees Celsius in mobile conditions, with minimal throughput sacrifices (9.8% and 8.5% respectively). It consistently maintained high throughput levels, proving the feasibility of achieving thermal efficiency without compromising network performance.
The second system focused on creating a reconfigurable antenna with a tunable operating frequency ranging from 6 GHz to 28 GHz. The antenna consists of multiple elements connected by Microelectromechanical Systems (MEMS) switches. Detailed studies were conducted on the impact of the location, dimension, and number of MEMS switches on the antenna's performance. The implementation of a 3x3 antenna array successfully demonstrated frequency tunability from 6 GHz to 28 GHz, achieving an S11 parameter lower than -10 dB, which indicates excellent performance and potential for wide-ranging applications in 5G networks.
The third system focused on optimizing the deployment of mmWave picocells through the correlation of visual cues and mmWave reflection profiles. It involved developing a mobile mmWave imaging platform and components capable of imaging through obstructions to facilitate object detection and link predictions. The project included a machine-learning aided model to map depth and color to reflections, and automatic localization and object-tagging modules for various applications, such as robot navigation and VR/AR games. Evaluation of this system under various channel conditions showed significant improvements in picocell placement accuracy and networking performance, thereby reducing link-outage probability and enhancing overall network reliability.
These outcomes highlight the project's success in demonstrating the potential of software-hardware co-design for reconfigurable millimeter-wave networks and sensing applications. The findings pave the way for future research and development in this promising field, emphasizing the project's contribution to advancing wireless communication technologies. The practical implications of this research extend to enhancing the performance and reliability of 5G and beyond-5G networks, as well as enabling new applications in areas like virtual reality, autonomous navigation, and efficient network deployments.
The project has provided extensive opportunities for training and professional development for several Ph.D. and undergraduate students. Students received initial research training, engaged in competitions, and presented their work at prominent conferences like ACM MobiCom, IEEE SECON, and ACM UbiComp. These activities fostered a high level of excitement among students, many of whom plan to continue this research long-term. Topics from the project have been integrated into advanced graduate-level IoT courses, sparking new research ideas, particularly in applying hardware-software reconfigurable design to higher-frequency mmWave networks and sensing. Several students received awards, travel grants, and recognitions, highlighting the project's impact on their professional growth.
The project's results have been widely disseminated to the broader community through multiple channels. Papers and posters were presented at various prestigious conferences, such as IEEE Antenna and Propagation Symposium, ACM HotMobile, IEEE ICNP, ACM MobiCom, IEEE SECON, ACM UbiComp, and ACM MobiSys. The project also led to several patent applications and a US trademark application, demonstrating its innovative contributions. Additionally, the team released code and datasets on their project website, ensuring that their findings are accessible to the wider research community. Invited presentations at seminars and conferences further extended the project's reach, facilitating knowledge sharing and collaboration with other researchers and industry professionals. This widespread dissemination underscores the project's significant impact on advancing the field of millimeter-wave networks and sensing.
Last Modified: 08/03/2024
Modified by: Sanjib Sur
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