The Rayleigh Fading Channel Prediction via Deep Learning

Algorithm 1

1. The weight matrices , are initialized randomly from 0 to 1. The threshold vectors ,

initialized to 0. Set the training goal and learning rate a reasonable value, respectively;

2. Input the channel information training set .

3. while do:

4. Calculate , and the , of the loss function and cost function

according to equation (7);

5. According to equation (8), the gradient of the output layer weight matrix and the

gradient of the threshold are calculated respectively;

6. The weight matrix of the hidden layer and the gradient of the threshold vector are calculated

are calculated according to (9);

7. Update the weight matrix of the hidden matrix and the output layer and the threshold

vectors ;

8. End while

9. Input the channel information test set and calculate the NMSE according to (16).