An interdisciplinary team of Rutgers researchers led by WINLAB Distinguished Professor Narayan Mandayam (PI) along with co-PIs Chung-Tse Michael Wu (Assistant Professor, ECE), Ruo-Qian Wang (Assistant Professor, CEE) and Joseph Brodie (Director of Atmospheric Sciences) are the recipients of an award from the National Science Foundation under the Spectrum and Wireless Innovation enabled by Future Technologies (SWIFT) program for the project "Enabling Spectrum Coexistence of 5G mmWave and Passive Weather Sensing." This three-year project funded at $750,000 addresses an emerging topic of increasing interest, namely the opening up of newer and higher spectrum for communication uses and the unintended effects on passive devices and legacy services not directly related to communications.
The project focuses on the utilization of newer spectrum in the mmWave bands that had not been previously allocated for commercial wireless applications, and studies the impact on collocated or adjacent spectrum utilized for other services, as well as strategies for mitigation of undesired impacts. 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 develop cross layer mitigation strategies including antennas/circuit (filtenna) design and direct modulation based beam steering that is integrated with cooperative MAC, networking and power control algorithms needed to enable coexistence between 5G services and weather prediction, as well as improved weather prediction algorithms. The team will investigate algorithm designs, reference architectures, and experiments on the
COSMOS testbed that will provide pointers to engineering methodology for the design of spectrally and system power-efficient 5G and Beyond 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.
More details on the project can be found at the NSF page
here.
Congratulations to the team!
