TY - GEN
T1 - Spectrum Sharing via Collaborative RFI Cancellation for Radio Astronomy
AU - Careem, Maqsood
AU - Chakaraborty, Shuvam
AU - Dutta, Aveek
AU - Saha, Dola
AU - Hellbourg, Gregory
N1 - Publisher Copyright: © 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Radio frequency Interference (RFI) from cellular and other communication networks is commonly mitigated at the Radio Telescope without any active collaboration with the interfering sources. The expanding Universe and simultaneous proliferation of Earth based and LEO communication infrastructure is causing unprecedented RFI that require collaborative strategies to maintain the scientific and societal goal of each. In this work, we provide a method of signal characterization and its use in subsequent cancellation, that uses Eigenspaces derived from the astronomical and the RFI signals. This is different from conventional time-frequency domain analysis, which is limited to fixed characterizations (e.g., complex exponential in Fourier methods) that cannot adapt to the changing statistics (e.g., autocorrelation) of the RFI, typically observed from communication systems. Through our analysis and simulation using real-world astronomical signals, we are able to remove RFI from cellular networks by 89.04%, which reduces excision at the Telescope.
AB - Radio frequency Interference (RFI) from cellular and other communication networks is commonly mitigated at the Radio Telescope without any active collaboration with the interfering sources. The expanding Universe and simultaneous proliferation of Earth based and LEO communication infrastructure is causing unprecedented RFI that require collaborative strategies to maintain the scientific and societal goal of each. In this work, we provide a method of signal characterization and its use in subsequent cancellation, that uses Eigenspaces derived from the astronomical and the RFI signals. This is different from conventional time-frequency domain analysis, which is limited to fixed characterizations (e.g., complex exponential in Fourier methods) that cannot adapt to the changing statistics (e.g., autocorrelation) of the RFI, typically observed from communication systems. Through our analysis and simulation using real-world astronomical signals, we are able to remove RFI from cellular networks by 89.04%, which reduces excision at the Telescope.
KW - Passive spectrum sharing
KW - Radio astronomy
KW - Radio frequency interference mitigation
UR - https://www.scopus.com/pages/publications/85125310241
U2 - 10.1109/DySPAN53946.2021.9677077
DO - 10.1109/DySPAN53946.2021.9677077
M3 - Conference contribution
T3 - 2021 IEEE International Symposium on Dynamic Spectrum Access Networks, DySPAN 2021
SP - 97
EP - 104
BT - 2021 IEEE International Symposium on Dynamic Spectrum Access Networks, DySPAN 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Symposium on Dynamic Spectrum Access Networks, DySPAN 2021
Y2 - 13 December 2021 through 15 December 2021
ER -