| CPC G06N 3/04 (2013.01) [H04B 7/18513 (2013.01); H04L 41/147 (2013.01); H04W 4/021 (2013.01)] | 20 Claims |

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1. A method for predicting rain fade for a rain zone using a deep learning system comprising a computer processor, the method comprising:
training a Neural Network (NN) by importing into the NN a training set of image information and beacon information, wherein the image information comprises image datasets comprising of a cloud view of an Area of Interest (AoI), a geolocation and a timestamp, and the beacon information comprises beacon datasets comprising a beacon strength, a current rain fade state, a geolocation and a timestamp;
receiving, at a receiver, a live beacon;
pre-processing to homogenize and to extract spatially and temporally matching data for the AoI from a live image information and a live beacon information comprising power measurements of the live beacon at the receiver; and
forecasting a rain fade based on the data in a near-future,
wherein the geolocation of one or more of the beacon datasets is located within the AoI,
a beacon periodicity of the live beacon information is less than or equal to five (5) minutes,
the pre-processing flattens a portion of the live image information from 3-dimensional or 2-dimensional information to 1-dimensional information, and
an image periodicity of the live image information is less than or equal to five (5) minutes.
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