Award Abstract # 1827940
PAWR Platform POWDER-RENEW: A Platform for Open Wireless Data-driven Experimental Research with Massive MIMO Capabilities

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: NORTHEASTERN UNIVERSITY
Initial Amendment Date: April 2, 2018
Latest Amendment Date: February 18, 2025
Award Number: 1827940
Award Instrument: Cooperative Agreement
Program Manager: Abraham Matta
amatta@nsf.gov
 (703)292-4624
CNS
 Division Of Computer and Network Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: April 1, 2018
End Date: March 31, 2026 (Estimated)
Total Intended Award Amount: $17,529,856.00
Total Awarded Amount to Date: $25,127,344.00
Funds Obligated to Date: FY 2018 = $4,369,587.00
FY 2019 = $4,379,471.00

FY 2020 = $6,726,893.00

FY 2021 = $3,669,430.00

FY 2022 = $2,781,965.00

FY 2023 = $3,199,998.00
History of Investigator:
  • Tommaso Melodia (Principal Investigator)
    melodia@northeastern.edu
Recipient Sponsored Research Office: Northeastern University
360 HUNTINGTON AVE
BOSTON
MA  US  02115-5005
(617)373-5600
Sponsor Congressional District: 07
Primary Place of Performance: Northeastern University
Boston
MA  US  02115-5005
Primary Place of Performance
Congressional District:
07
Unique Entity Identifier (UEI): HLTMVS2JZBS6
Parent UEI:
NSF Program(s): SII-Spectrum Innovation Initia,
TIP-CHIPS KTA-6 Communications,
CISE Research Resources,
Networking Technology and Syst
Primary Program Source: 01001920DB NSF RESEARCH & RELATED ACTIVIT
01002223DB NSF RESEARCH & RELATED ACTIVIT

01001819DB NSF RESEARCH & RELATED ACTIVIT

01002223DB NSF RESEARCH & RELATED ACTIVIT

01002122DB NSF RESEARCH & RELATED ACTIVIT

01002324DB NSF RESEARCH & RELATED ACTIVIT

01002021DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 044Z, 9251, 4444
Program Element Code(s): 151Y00, 272Y00, 289000, 736300
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070, 47.084

ABSTRACT

This project creates a city-scale platform for advanced wireless research that will be deployed over the period 2018 - 2023 in Salt Lake City, Utah. This Platform for Open Wireless Data-driven Experimental Research (POWDER) supports at-scale experimentation of novel advanced wireless broadband and communication technologies in the sub-6 GHz band. The project features interactions with regional networks encompassing initiatives on public transportation, broadband delivery, education and health service delivery as well as advancement of science, technology and research by creating an ecosystem of a hundred small companies in allied technical domains. The ability to use this platform by early adopter companies/startups and application developers to evaluate technologies in their pre-commercial phase will have a significant positive impact on the speed of innovation in the data networking and application domains. This effort will also benefit educators and students at all levels of study in communications-related disciplines.

A key feature of the platform is the partnership with the Reconfigurable Eco-system for Next-generation End-to-end Wireless (RENEW) project at Rice University to develop a highly programmable and flexible massive multi-input multi-output (MIMO) platform that is an essential feature of both 5G and beyond-5G wireless networks. The platform will feature (i) heterogeneous systems composed of programmable base stations, mobile devices and static sensors; (ii) state of the art massive MIMO base-stations; (iii) ability to conduct research over a diverse spectrum range (from 50 MHz to 3.8 GHz), and (iv) a large-scale software defined wireless networking testbed integrated with an existing NSF-funded cloud testbed, thereby enabling end-to-end experimentation. Another unique aspect of the platform is support for wireless mobility-based studies, provided by using couriers with predictable movement patterns (e.g., buses), less predictable but bounded mobility (e.g., maintenance vehicles), and controllable couriers (e.g., on-site volunteers). Each of these deployed units will consist of "base" functionality that includes user-programmable software defined radios, "bring your own device" (BYOD) experiments, and will be connected via a sophisticated platform control framework. Existing fiber links will connect the wireless base stations to about half a dozen edge compute platforms. This will enable complex device provisioning and a set of tools for scientific workflow management, collaboration, and artifact sharing, with a goal towards promoting rigorous standards for reproducibility in this field.

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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(Showing: 1 - 10 of 39)
Varner, Michael A. and Rodriguez, Thomas A. and Durgin, Gregory D. "RF Coverage Mapping of Bistatic Radio Links Using the Terrain Integrated Rough Earth Model (TIREM)" 2022 16th European Conference on Antennas and Propagation (EuCAP) , 2022 https://doi.org/10.23919/EuCAP53622.2022.9768971 Citation Details
Johnson, David and Maas, Dustin and Van Der Merwe, Jacobus "Open source RAN slicing on POWDER: a top-to-bottom O-RAN use case" ACM MobiSys 2021 , 2021 https://doi.org/10.1145/3458864.3466912 Citation Details
Larrea, Jon and Marina, Mahesh K. and Van der Merwe, Jacobus "Nervion: a cloud native RAN emulator for scalable and flexible mobile core evaluation" ACM MobiCom 2021 , 2021 https://doi.org/10.1145/3447993.3483248 Citation Details
Liu, Zhecun and Dasala, Keerthi Priya and Mu, Di and Doost-Mohammady, Rahman and Knightly, Edward W. "M3A: Multipath Multicarrier Misinformation to Adversaries" , 2023 https://doi.org/10.1145/3570361.3613282 Citation Details
Mitchell, Frost and Baset, Aniqua and Patwari, Neal and Kasera, Sneha Kumar and Bhaskara, Aditya "Deep Learning-based Localization in Limited Data Regimes" Proc. of the ACM Workshop on Wireless Security and Machine Learning (WiseML 2022) , 2022 https://doi.org/10.1145/3522783.3529529 Citation Details
Mitchell, Frost and Bhaskara, Aditya and Wang, Jie and Patwari, Neal "Less is More: Improved Path Loss Prediction Using Simple Interpolation Models" , 2024 https://doi.org/10.1109/DySPAN60163.2024.10632815 Citation Details
Mitchell, Frost and Patwari, Neal and Bhaskara, Aditya and Kasera, Sneha Kumar "Learning-based Techniques for Transmitter Localization: A Case Study on Model Robustness" , 2023 https://doi.org/10.1109/SECON58729.2023.10287483 Citation Details
Mitchell, Frost and Smith, Phillip and Bhaskara, Aditya and Kasera, Sneha Kumar "Exploring Adversarial Attacks on Learning-based Localization" , 2023 https://doi.org/10.1145/3586209.3591398 Citation Details
Mitchell, Frost and Wang, Jie and Bhaskara, Aditya and Kasera, Sneha Kumar "Utilizing Confidence in Localization Predictions for Improved Spectrum Management" , 2024 https://doi.org/10.1109/DySPAN60163.2024.10632736 Citation Details
Monterroso, Jose and Van der Merwe, Jacobus and Webb, Kirk and Wong, Gary "Towards using the POWDER platform for RF propagation validation" IEEE CNERT 2021 , 2021 https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484469 Citation Details
Sarbhai, Aarushi and Mitchell, Frost and Kasera, Sneha and Bhaskara, Aditya and Van_der_Merwe, Jacobus and Patwari, Neal "Reactive Spectrum Sharing with Radio Dynamic Zones" , 2024 https://doi.org/10.1109/DySPAN60163.2024.10632820 Citation Details
(Showing: 1 - 10 of 39)

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