Award Abstract # 2128077
SWIFT: Enabling Spectrum Coexistence of 5G mmWave and Passive Weather Sensing

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: RUTGERS, THE STATE UNIVERSITY
Initial Amendment Date: August 24, 2021
Latest Amendment Date: October 19, 2022
Award Number: 2128077
Award Instrument: Standard Grant
Program Manager: Murat Torlak
mtorlak@nsf.gov
 (703)292-0000
CNS
 Division Of Computer and Network Systems
CSE
 Direct For Computer & Info Scie & Enginr
Start Date: October 1, 2021
End Date: September 30, 2024 (Estimated)
Total Intended Award Amount: $750,000.00
Total Awarded Amount to Date: $750,000.00
Funds Obligated to Date: FY 2021 = $750,000.00
History of Investigator:
  • Narayan Mandayam (Principal Investigator)
    narayan@winlab.rutgers.edu
  • Chung-Tse Wu (Co-Principal Investigator)
  • Ruo-Qian Wang (Co-Principal Investigator)
  • Joseph Brodie (Co-Principal Investigator)
Recipient Sponsored Research Office: Rutgers University New Brunswick
3 RUTGERS PLZ
NEW BRUNSWICK
NJ  US  08901-8559
(848)932-0150
Sponsor Congressional District: 12
Primary Place of Performance: Rutgers, The State of New Jersey
671 US Highway 1
North Brunswick
NJ  US  08902-3390
Primary Place of Performance
Congressional District:
12
Unique Entity Identifier (UEI): M1LVPE5GLSD9
Parent UEI:
NSF Program(s): SII-Spectrum Innovation Initia
Primary Program Source: 01002122DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 1207, 7697, 7976
Program Element Code(s): 151Y
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

The demand for increasingly higher wireless data rates in 5G and Beyond 5G (B5G) developments has led to the utilization of newer spectrum in the mmWave bands that had not been previously allocated for commercial wireless applications. Such new spectrum opportunities often come with speculation when it relates to impacting collocated or adjacent spectrum utilized for other services. Specifically, the 5G band allocated in the 26 GHz spectrum referred to as 3GPP band n258 has generated anxiety and concern in the meteorological data forecasting community including the National Oceanic and Atmospheric Administration (NOAA). This issue stems from 5G transmissions impacting the observations of passive sensors on weather satellites used to detect the amount of water vapor in the atmosphere, which in turn affects weather forecasting and predictions. To this end, the proposed research project aims to tackle this issue by characterizing the impact of 5G transmissions on weather data measurements and prediction, and then design cross layer mitigation strategies needed to enable coexistence between 5G services and weather prediction, as well as improved weather prediction algorithms. Furthermore, undergraduate, graduate and high school students including underrepresented minority groups will be engaged and trained in the coexistence of 5G with passive sensing and weather forecasting.

The project will lead to algorithm designs, reference architectures, and testbed experiments that will provide pointers to engineering methodology for the design of spectrally and system power-efficient 5G/B5G networks that can peacefully coexist with passive weather sensors. It will also enable the development of improved weather forecasting algorithms that are cognizant of the potential impact of unintended interference. The specific research tasks entail: (i) designing improved models for characterizing the 5G impact on radiance using both simulation and analysis based approaches taking into account transmit power levels, specific sub-band occupancy, transmit modulation schemes, nonlinearity of power amplifiers, and absorption and transmission through layers of clouds and atmosphere; (ii) mapping the spatial density of 5G transmitters, and the elevation and directionality of transmissions to geospatial sensitivity to leakage; (iii) devising novel cross-layer approaches for mitigating the 5G impact on 23.8 GHz using antennas/circuit (filtenna) design and direct modulation based beam steering that is integrated with cooperative MAC and networking strategies along with power control; (iv) developing improved weather prediction algorithms that are designed to be robust to 5G leakage; and (v) experimenting on the PAWR COSMOS testbed to study adjacent channel leakage from 5G transmissions.

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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Majumdar, Ishani B. and Vosoughitabar, Shaghayegh and Michael Wu, Chung-Tse and Mandayam, Narayan B. and Brodie, Joseph F. and Golparvar, Behzad and Wang, Ruo-Qian "Resource Allocation Using Filtennas in the Presence of Leakage" 2022 IEEE Future Networks World Forum (FNWF) , 2022 https://doi.org/10.1109/FNWF55208.2022.00109 Citation Details

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