Microwave radiometric characterization of deep space ka-band channel from numerical models and experimental ground data

The increasing demand for high data rate services of space exploration missions lead to the designation of the downlink Ka frequency band (31.8 – 32.3 GHz) as the standard for deep space telecommunications. This paved the way to a new era of deep space exploration programs, with respect to the more conventional X frequency band (~8.4 GHz). This choice is supported by two main reasons: i) a 16x factor improvement in the power strength (due to the squared-frequency law increase of antenna directivity of the downlink beam for the same antenna effective area)going from X-band to Ka-band; ii) a 50x factor in allocated bandwidth for deep space communications (500 MHz at Ka-band, 10 MHz at X-band), leading to an increase of the actual transmitted data per unit of time (throughput) when using Ka-band. However, the main drawback when using Ka-band is due to the weather effects (rain precipitation above all), which cause much larger fluctuations on Ka-band than on X-band. The traditional method of increasing the transmitted power (power margins) to compensate these fluctuations is wasteful of energy for deep space Ka-band. Therefore, a different operations concept is needed for Ka-band links.In this context, the aim of this work is to investigate weather effects on the propagation of Ka-band signals in a typical deep-space transmission link in order to prompt transmission data-rate adaptation strategies based on the knowledge of the link channel conditions from the present to future instants. To achieve the aforementioned goal, we make use of a weather forecast model (WFM), a radiopropagation model (RPM) and a downlink budget model (DBM) set up in the area of Cebreros, Spain where an European Space Agency ground station for deep space communication is located. WFM, RPM and DBM are bound together to forecast weather scenarios. The WFM provides the atmospheric state (i.e. pressure, humidity temperature, rain, etc.). The RPM exploit the atmospheric state to derive the expected channel state and its effects on the propagating signal(i.e. path attenuation, brightness temperature). Finally, the DBM converts these effects into expected transferred data volume (i.e. probability of correct transmission and data loss). More in details, the adopted WFM is the Mesoscale Model (MM5), where as the RPM is a physically-based radio propagation model which makes use of a radiative transfer solver based on the Eddington approximation as well as accurate scattering module. The general idea for a future practical use in deep space communications is to exploit WFM, RPM and DBM to provide predictions of transmission channel scenarios to allow data rate adaptive strategies.The validation of the proposed modelling chain, based on simulation of the atmospheric related parameters, is performed against co-located ground-based microwave radiometer (MWR)observations. A multichannel MWR, working in the 22-58 GHz band is operating in Cebreros, providing reference measurements of Ka-band brightness temperature and path attenuation and estimates of the columnar integrated water vapour and liquid water contents. These quantities are of uppermost interest for assessing the precision and accuracy of the outputs of the WFM and RPM. A period of several months is considered as validation test, thus covering the seasonal variability of selected target area. The presentation gives an overview of the main results, highlighting the improvement achieved with respect to more conventional transmission strategies, and indicating the accuracy interval of the forecasts in terms of transferred data throughput.