US 12,238,190 B2
Method of performing communication load balancing with multi-teacher reinforcement learning, and an apparatus for the same
Jikun Kang, Montreal (CA); Xi Chen, Montreal (CA); Chengming Hu, Montreal (CA); Ju Wang, Brossard (CA); Gregory Lewis Dudek, Westmount (CA); and Xue Liu, Montreal (CA)
Assigned to SAMSUNG ELECTRONICS CO., LTD., Suwon-si (KR)
Filed by SAMSUNG ELECTRONICS CO., LTD., Suwon-si (KR)
Filed on Jul. 12, 2023, as Appl. No. 18/351,201.
Application 18/351,201 is a continuation of application No. 17/957,811, filed on Sep. 30, 2022, granted, now 11,750,719.
Claims priority of provisional application 63/253,089, filed on Oct. 6, 2021.
Prior Publication US 2023/0353659 A1, Nov. 2, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. H04L 67/5682 (2022.01); H04L 41/16 (2022.01); H04L 67/1004 (2022.01)
CPC H04L 67/5682 (2022.05) [H04L 41/16 (2013.01); H04L 67/1004 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A server for obtaining a load balancing artificial intelligence (AI) model for a plurality of base stations in a communication system, the server comprising:
at least one memory storing instructions; and
at least one processor configured to execute the instructions to:
obtain a plurality of teacher models based on a plurality of traffic data sets collected from the plurality of base stations, respectively;
obtain a plurality of student models based on knowledge distillation from the plurality of teacher models, wherein the plurality of student models is trained based on a knowledge distillation loss that represents a difference between a teacher prediction of the plurality of teacher models and a student prediction of the plurality of student models, and
obtain the load balancing AI model for the plurality of base stations based on the plurality of student models.