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.
|Title of host publication||IVMSP 2022 - 2022 IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||5|
|State||Published - 2022|
|Event||14th IEEE Image, Video, and Multidimensional Signal Processing Workshop, IVMSP 2022 - Nafplio, Greece|
Duration: 26 Jun 2022 → 29 Jun 2022
|Name||IVMSP 2022 - 2022 IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop|
|Conference||14th IEEE Image, Video, and Multidimensional Signal Processing Workshop, IVMSP 2022|
|Period||26/06/22 → 29/06/22|
Bibliographical noteFunding Information:
This work was supported in part by the NSF-BSF grant number CNS-1910757. We would also like to thank Yoav Ludmer and Menachem Loberboum from SMBIT LTD. for providing the data
© 2022 IEEE.
- Commercial Microwave Links (CMLs)
- Rain Estimation
- Rain Maps