@article{3029081,
    title = "Multi-Hop RIS-Empowered Terahertz Communications: A DRL-Based Hybrid
Beamforming Design",
    author = "Huang, Chongwen and Yang, Zhaohui and Alexandropoulos, George C. and and Xiong, Kai and Wei, Li and Yuen, Chau and Zhang, Zhaoyang and Debbah, and Merouane",
    journal = "IEEE Journal on Selected Areas in Communications",
    year = "2021",
    volume = "39",
    number = "6",
    pages = "1663-1677",
    publisher = "IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC",
    issn = "0733-8716, 1558-0008",
    doi = "10.1109/JSAC.2021.3071836",
    keywords = "Array signal processing; Attenuation; Wireless communication; Spread
spectrum communication; Relays; Optimization; Nonlinear optics;
Terahertz communication; reconfigurable intelligent surface; 6G;
Massive-MIMO; multi-hop; multiuser; beamforming; deep reinforcement
learning; alternating optimization",
    abstract = "Wireless communication in the TeraHertz band (0.1-10 THz) is envisioned
as one of the key enabling technologies for the future sixth generation
(6G) wireless communication systems scaled up beyond massive multiple
input multiple output (Massive-MIMO) technology. However, very high
propagation attenuations and molecular absorptions of THz frequencies
often limit the signal transmission distance and coverage range.
Benefited from the recent breakthrough on the reconfigurable intelligent
surfaces (RIS) for realizing smart radio propagation environment, we
propose a novel hybrid beamforming scheme for the multi-hop RIS-assisted
communication networks to improve the coverage range at THz-band
frequencies. Particularly, multiple passive and controllable RISs are
deployed to assist the transmissions between the base station (BS) and
multiple single-antenna users. We investigate the joint design of
digital beamforming matrix at the BS and analog beamforming matrices at
the RISs, by leveraging the recent advances in deep reinforcement
learning (DRL) to combat the propagation loss. To improve the
convergence of the proposed DRL-based algorithm, two algorithms are then
designed to initialize the digital beamforming and the analog
beamforming matrices utilizing the alternating optimization technique.
Simulation results show that our proposed scheme is able to improve 50%
more coverage range of THz communications compared with the benchmarks.
Furthermore, it is also shown that our proposed DRL-based method is a
state-of-the-art method to solve the NP-hard beamforming problem,
especially when the signals at RIS-assisted THz communication networks
experience multiple hops."
}