Although the deployment of 5G networks has already started, there are still open questions regarding propagation at millimeter-wave frequency bands. Several propagation campaigns have been carried out at several bands previously identified by regulatory organizations, but due to the wide range of allocated segments of spectrum and the variety of possible propagation scenarios, more measurement campaigns are needed. In this regard, the Universidad Politécnica de Madrid (UPM) has taken millimeter-wave measurements at 26, 32, and 39 GHz bands in an indoor corridor scenario in line-of-sight (LOS) conditions with two antenna configurations (a horn antenna has been used in transmission whereas horn and omnidirectional antennas have been used in reception), and the main results are presented in this paper. The obtained path loss results have been compared with existing millimeter-wave propagation models.

This contribution presents a comprehensive methodology for the real-time estimation of the rain intensity from downlink satellite signals. The enhanced system leverages on extremely randomized tree classifiers to automatically perform rainfall detection along earth–satellite links and successively employs an improved procedure to determine the corresponding slant-path rain attenuation. The latter quantity is then exploited to yield real-time rainfall rate estimates with a 1-min time resolution. The accuracy of the proposed methodology is tested using the Ka - and $Q$ -band propagation data, collected in two different sites (Milan and Madrid) and in the framework of the propagation experiments. The results demonstrate the reliability of the automated rain event detector, as well as a satisfactory accuracy in estimating the slant-path rain attenuation and the point rainfall rate. The accuracy is assessed both on a statistical and on an instantaneous basis through the evaluation of different error figures and by inspection of individual time series.

The use of frequencies well into the EHF band (30-300 GHz) is a key element in 5G and beyond technologies. Rain attenuation is the major impairment affecting terrestrial radio links in this band. In the absence of enough experimental measurements, rain attenuation can be estimated by using physical models of radiowave scattering in rain drops combined with information about the rain Drop Size Distributions (DSD). In this work, the characterization of rain attenuation in the 80-200 GHz frequency range is carried out from a large database of twelve years of experimental DSD gathered in Madrid, Spain. Rain attenuation is estimated for each collected minute of rain using two approaches: a first one based on the assumption of raindrops as spherical and the application of the Mie theory, and a second one that uses a non-spherical raindrop model and electromagnetic simulations and is consequently more realistic. The main results show that the currently used ITU-R model generally underestimates rain specific attenuation; the influence of polarization becomes smaller and negligible as frequency approaches 200 GHz; and rain specific attenuation significantly varies due to the spread of the DSD. Moreover, a model for this variability of rain attenuation is also proposed.

The use of millimeter wave Q/V bands in satellite communications is expected to grow in the near future. At these frequency bands rain is the main contribution to atmospheric losses, although the effect of clouds is also relevant. Propagation models dealing with attenuation produced by clouds are not widely validated by experimental data, because of the difficulty of isolating cloud attenuation from other propagation effects. This paper presents a novel method used to derive cloud attenuation in the absence of rain from Q-band excess attenuation measurements collected at Universidad Politécnica de Madrid, taking advantage of ancillary data from two co-located instruments: a disdrometer and a Ka-band beacon receiver. Using this procedure, time series of Q-band cloud attenuation have been extracted for a period of 5 years and the calculated statistical results have been compared to estimations derived from different models. Cloud attenuation statistics derived from measurements with this novel procedure are in good agreement with radiosounding-based models, whereas Rec. ITU-R P.840 model overestimate them. The use of the ERA5 TCLW (Total Column Cloud Liquid Water) time series are considered as suitable input data for cloud attenuation estimation, with results similar to those obtained from radiosounding observations.