@inproceedings{c9adc3f029ff49d0ab76258f72a6ca39,
title = "Beamforming Based on DRL for STAR-RIS Aided Cell-Free Massive MIMO Network",
abstract = "The cell-free massive multiple-input multiple-output (CF mMIMO) network is emerging as an innovative technology that utilizes numerous access points (APs) distributed across a region to provide services for users through coherent transmission and reception. To enhance the coverage of the CF mMIMO network, we introduce simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) into the CF mMIMO network. In the STAR-RIS aided CF mMIMO network, beamforming for the downlink of mobile users becomes exceptionally complex and challenging. Therefore, we propose a beamforming algorithm based on soft actor-critic (SAC), which can jointly optimize the beamforming of APs and phase shifts and amplitude coefficients of STAR-RISs. Simulation results demonstrate that the proposed SAC-based beamforming algorithm significantly maximizes the sum-rate of the STAR-RIS aided CF mMIMO network, outperforming the no STAR-RIS aided CF mMIMO network in terms of meeting quality of service (QoS) requirement.",
keywords = "cell-free massive MIMO, deep reinforcement learning (DRL), simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)",
author = "Zhichao Gao and Ruikang Zhong and Xidong Mu and Ju Liu and Yuanwei Liu",
year = "2025",
month = mar,
day = "11",
doi = "10.1109/GLOBECOM52923.2024.10901346",
language = "English",
series = "Proceedings - IEEE Global Communications Conference, GLOBECOM",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1173--1178",
booktitle = "GLOBECOM 2024 - 2024 IEEE Global Communications Conference: proceedings",
address = "United States",
note = "2024 IEEE Global Communications Conference, GLOBECOM 2024 ; Conference date: 08-12-2024 Through 12-12-2024",
}