Transfer learning of network traffic prediction model among cellular base stations

A method for managing traffic prediction model transfer learning among 5G base stations, the method comprising:

• receiving a first plurality of base station statistics, wherein the first plurality of base station statistics includes a first data set of a first size from a first base station;
• receiving a second plurality of base station statistics, wherein the second plurality of base station statistics includes a second data set of a second size corresponding to a second base station;
• selecting the first base station as a source base station;
• training a similarity network;
• receiving a source prediction model from the first base station and an importance score matrix;
• receiving a prediction model request from a target base station, wherein the target base station is the second base station;
• computing a first similarity using the similarity network;
• obtaining a first scaled importance score matrix based on the importance score matrix and based on the first similarity;
• and
• sending the source prediction model and the first scaled importance score matrix to the second base station.

A non-transitory computer readable medium configured to store a program, wherein execution of the program by one or more processors of a server is configured to cause the server to at least:

• receive a first plurality of base station statistics, wherein the first plurality of base station statistics includes a first data set of a first size from a first base station;
• receive a second plurality of base station statistics, wherein the second plurality of base station statistics includes a second data set of a second size corresponding to a second base station;
• select the first base station as a source base station;
• train a similarity network;
• receive a source prediction model from the first base station and an importance score matrix;
• receive a prediction model request from a target base station, wherein the target base station is the second base station;
• compute a first similarity using the similarity network;
• obtain a first scaled importance score matrix based on the importance score matrix and based on the first similarity;
• and
• send the source prediction model and the first scaled importance score matrix to the second base station,
• whereby the second base station is configured to use the source prediction model, and the first scaled importance score matrix to generate a target prediction model and predict radio system parameters relevant to the second base station, wherein the radio system parameters include a future value of user data traffic passing through the second base station.