公开(公告)号：US20240204843A1

公开(公告)日：2024-06-20

申请号：US18343546

申请日：2023-06-28

Applicant: Korea Advanced Institute of Science and Technology

Inventor： Hyuncheol PARK ,  Seunghun LEE

IPC: H04B7/06 ,  H04B7/0452 ,  H04B17/336

CPC classification number: H04B7/0626 ,  H04B7/0452 ,  H04B17/336

Abstract: Disclosed is a method and system for interference control and hybrid beamforming using multi-agent deep reinforcement learning for multiple users. The disclosed method includes performing multi-agent reinforcement learning using interference and antenna gain information that is expected based on a gain table designed using channel state information (CSI) of all user equipments; searching for an analog beamforming matrix pair corresponding to a link that maximizes antenna gain and minimizes interference between user equipments through multi-agent reinforcement learning; applying a signal-to-leakage plus noise ratio (SLNR) maximization technique that minimizes the interference between the user equipments based on the link; and optimizing transmission (Tx) power for each link based on iterative water-filling.