The results from 1 year of data collected during an electromagnetic wave propagation experiment at {E} -band are presented. The research activity originates from the collaboration between Politecnico di Milano, Milan, Italy, and the Huawei European Microwave Centre in Milan, which installed short (325 m) terrestrial links operating at 73 and 83 GHz, connecting two buildings in the university main campus. The received power data are processed, using a novel approach, to identify rain events and to remove the wet antenna effect, with the aim of accurately quantifying the fade induced by precipitation, A_{R}. Moreover, A_{R} is estimated by taking advantage of the ancillary data collected by the laser-based disdrometer collocated with the link transceivers. The results definitely point out the higher prediction accuracy achieved by exploiting the information on the rain drop size. A full year of data are used as reference to test the accuracy of the statistical prediction model for terrestrial links currently recommended by the ITU-R, which reveals a large overestimation. Finally, alternative models providing a higher accuracy are proposed and their accuracy assessed.
The Impact of Rain on Short {E} -Band Radio Links for 5G Mobile Systems: Experimental Results and Prediction Models
Luini L.;Riva C. G.
2020-01-01
Abstract
The results from 1 year of data collected during an electromagnetic wave propagation experiment at {E} -band are presented. The research activity originates from the collaboration between Politecnico di Milano, Milan, Italy, and the Huawei European Microwave Centre in Milan, which installed short (325 m) terrestrial links operating at 73 and 83 GHz, connecting two buildings in the university main campus. The received power data are processed, using a novel approach, to identify rain events and to remove the wet antenna effect, with the aim of accurately quantifying the fade induced by precipitation, A_{R}. Moreover, A_{R} is estimated by taking advantage of the ancillary data collected by the laser-based disdrometer collocated with the link transceivers. The results definitely point out the higher prediction accuracy achieved by exploiting the information on the rain drop size. A full year of data are used as reference to test the accuracy of the statistical prediction model for terrestrial links currently recommended by the ITU-R, which reveals a large overestimation. Finally, alternative models providing a higher accuracy are proposed and their accuracy assessed.File | Dimensione | Formato | |
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