Abstract
A Power-Law relation between attenuation and rain rate has proven to be a useful tool in wireless network design at microwave and mmWave frequencies. In the last decade this relation has also been used for estimating rain from signal level measurements in Commercial Microwave Links (CMLs). In this paper we empirically show that while the power-law relation provides good approximation for relating attenuation and rain-rate in terrestrial microwave links of length 1-20Km, for links shorter than 1km, widely used in 5G technologies, it shows significant errors. We then suggest a recurrent neural network (RNN) approach to relate attenuation with rain rate and we show that it overcomes the uncertainties in short links.
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