Factorization -Learning Initialization for Parameter Optimization in Cellular Networks

Algorithm 1

Factorization -learning initialization (FQI).

Input: Factorization threshold , latent factor , max iterations

1: Calculate the percentage of visited states through Eq. (7) and the increment of the percentage of visited states by Eq. (8).

2: If then

3:  Extract the visited entries from Q table as experiences triples.

4:  Concatenate the one hot encodings of state and action , respectively, in experience

 Tuples to form feature vector and take as the corresponding target.

5:  Estimate the model parameters at most iterations by Eq. (12).

6:  Complete the Q table via Eq. (9).

7:  Replace the original Q table with the factorized Q table.

8: End if