The present study deals with the development of a low cost microwave device devoted to measure average rain rate observed along earth - satellite links. The principle is to use rain atmospheric attenuation along Earth - space links in Ku-band to deduce the path averaged rain rate. These links are characterized by a path length of a few km through the troposphere. Ground based power measurements are carried out by receiving TV channels from different geostationary satellites in Ku-band. The major difficulty in this study is to retrieve rain characteristics among many fluctuations of the received signal which are due to atmospheric scintillations, changes in the composition of the atmosphere (water vapour concentration, cloud water content) or satellite features (variation of the emitted power, satellite motions). In order to perform a feasibility study of such a device, a measurement campaign has been performed for five months near Paris. This paper proposes an algorithm based on an artificial neural network to identify drought and rainy periods and to suppress the variability of the received signal due to no-rain effects. Taking into account the height of the rain layer, rain attenuation is then inverted to obtain path averaged rain rate. Obtained rainfall rates are compared with co-located rain gauges and radar measurements on the whole experiment period, then the most significant rainy events are analyzed.