Work

Reinforcement Learning-Based Multi-Agent Beam Tracking for Multi-RIS Hybrid Beamforming

Year: 2025

Type: article

Source: IEEE Transactions on Wireless Communications

DOI: 10.1109/twc.2025.3610047

Authors: Najam Us Saqib, Guopei Zhu, Sung Ho Chae, Changjun Zhou, Zhonglong Zheng, Sang-Woon Jeon

Institutions: Hanyang University, Kwangwoon University, Zhejiang Normal University

Language: English

Topic: Advanced Wireless Communication Technologies

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: closed

Funders: National Natural Science Foundation of China, National Research Foundation of Korea, Institute for Information and Communications Technology Promotion

Awards: G2624907594, G272747303, G3194693416

OpenAlex ID: W4414404793

FWCI: 0.68

Cites: 41

Cited by: 3

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