TY - GEN
T1 - Rain Estimation from Smart City's E-band Links
AU - Janco, Roy
AU - Ostrometzky, Jonatan
AU - Messer, Hagit
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Smart cities around the world are supported by high-capacity wireless communication networks, which are based on millimeter-waves links. The propagating waves are sensitive to hydrometeors, and their signal level is attenuated by rain. However, most of the links in such networks are shorter than 1 km, imposing large errors on the rain estimation results. In this paper we demonstrate, using actual measurements from the city of Rehovot, Israel, how high-resolution rain maps can be generated from the received signal level measurements collected by these links. We first propose a method for reducing the errors in converting signal attenuation to rainfall estimates in short, in-city links. The proposed method requires calibration of model parameters using side information from either a rain gauge or a long link in the vicinity of the network. We empirically analyze the results of the calibrating method using either auxiliary measurements and show that the performance is satisfactory for both. Then, we apply a spatial interpolation method on the rainfall resulting estimates, and demonstrate the construction of an high-resolution 2-D map of the accumulated rain in a city, a product with great potential for improving well-being of life in urban areas.
AB - Smart cities around the world are supported by high-capacity wireless communication networks, which are based on millimeter-waves links. The propagating waves are sensitive to hydrometeors, and their signal level is attenuated by rain. However, most of the links in such networks are shorter than 1 km, imposing large errors on the rain estimation results. In this paper we demonstrate, using actual measurements from the city of Rehovot, Israel, how high-resolution rain maps can be generated from the received signal level measurements collected by these links. We first propose a method for reducing the errors in converting signal attenuation to rainfall estimates in short, in-city links. The proposed method requires calibration of model parameters using side information from either a rain gauge or a long link in the vicinity of the network. We empirically analyze the results of the calibrating method using either auxiliary measurements and show that the performance is satisfactory for both. Then, we apply a spatial interpolation method on the rainfall resulting estimates, and demonstrate the construction of an high-resolution 2-D map of the accumulated rain in a city, a product with great potential for improving well-being of life in urban areas.
KW - Commercial Microwave Links (CMLs)
KW - Rain Estimation
KW - Rain Maps
KW - Smart-City
KW - mmWave
UR - http://www.scopus.com/inward/record.url?scp=85135154535&partnerID=8YFLogxK
U2 - 10.1109/IVMSP54334.2022.9816243
DO - 10.1109/IVMSP54334.2022.9816243
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AN - SCOPUS:85135154535
T3 - IVMSP 2022 - 2022 IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop
BT - IVMSP 2022 - 2022 IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th IEEE Image, Video, and Multidimensional Signal Processing Workshop, IVMSP 2022
Y2 - 26 June 2022 through 29 June 2022
ER -