Mobile Radio Networks and Weather Radars Dualism: Rainfall Measurement Revolution in Densely Populated Areas

Abstract

This study demonstrates, for the first time, how a network of cellular base stations (BSs) - the infrastructure of mobile radio networks - can be used as a distributed opportunistic radar for rainfall remote sensing. By adapting signal-processing techniques traditionally employed in Doppler weather radar systems, we demonstrate that BS signals can be used to retrieve typical weather radar products, including reflectivity factor, mean Doppler velocity, and spectral width. Due to the high spatial density of BS infrastructure in urban environments, combined with intrinsic technical features such as electronically steerable antenna arrays and wide receiver bandwidths, the proposed approach achieves unprecedented spatial and temporal resolutions, on the order of a few meters and several tens of seconds, respectively. Despite limitations related to low transmitted power, limited antenna gain, and other system constraints, a major challenge arises from ground clutter contamination, which is exacerbated by the nearly horizontal orientation of BS antenna beams. This work provides a thorough assessment of clutter impact and demonstrates that, through appropriate processing, the resulting clutter-filtered radar moments reach a satisfactory level of quality when compared with raw observations and with measurements from independent BSs with overlapped field-of-views. The findings highlight a transformative opportunity for urban hydrometeorology: leveraging existing telecommunications infrastructure to obtain rainfall information with a level of spatial granularity and temporal immediacy like never before.

Figures (15)

• Figure 1: Conceptual visualization of BS distribution reflecting the global coverage trends derived from publicly available sources and industry reports GSMA:2025OpenCelliD:2025ITU:2025Ookla:2025. Yellow/Orange areas indicate high density (urban regions in North America, Europe, East Asia). Dark green areas show moderate coverage. Sparse regions represent limited connectivity a); Weather radar coverage at 2019 (with permission from Saltikoff:2019b) in b).
• Figure 2: Conceptual figure of a base station (BS) in a typical communication mode (COM) in which BS serves the final mobile users (mobile devices in green) a); and the weather radar mode (WRM) in which BS antenna multi beams (orange lobes) scans a sectorial portion of the cell to intercept rain in the area covered b).
• Figure 3: Representation of time frame organization a) in the typical BS-COM working mode; b) in the experimental BS-WRM. Note that in panel a), downlink (DL) and uplink (UL) time slots are depicted as separate and contiguous slots for ease of illustration, whereas in practice they interleave using a more articulated pattern following the 3GPP standard.
• Figure 4: Block diagram of the clutter suppression algorithm used in the BS-WRM. Textured-filled boxes indicate input and output quantities, whereas those gray-shaded are the auxiliary input parameters.
• Figure 5: Representation of differential phase definition , $\phi(m,k;o,s)$ (f). The initial time sequence $x=x_g$ of $N_p'$ samples for a single g-th beam (a) is then processed separately in $N_p$-wide moving windows each of them spaced by a shift quantity $s$ (b). In a single window the time series of $N_p$ samples (c) is then divided in two distinct time series $x_1$ and $x_2$ as in eq. \ref{['eq:subsampling_x1']} and \ref{['eq:subsampling_x2']} of staggered samples (d), (e) orange and blue samples respectively, as a function of the offset $o$. Textured orange and blue samples in d) and e) are those discarded by the effects of the imposed offset.