 |
In this paper, a deep reinforcement learning (DRL) approach is used for the RIS beamforming design in the RIS-assisted multiple input multiple output (MIMO) communication to maximize the system sum rate in the downlink transmission. The main contributions of this paper are summarized as follows. We consider the hardware loss of RIS and propose a phase shift design for RIS-assisted MIMO communication. We design a DRL based RIS beamforming algorithm for the above scheme, by introducing interference signals and interfering with action selection to prevent from falling into local optimal solutions, and the simulation results show that the proposed algorithm has a significant improvement over the typical algorithm.
|
IEEE/ICACT20240375 Slide.04
[Big Slide]
[YouTube]