Terahertz Massive MIMO with Holographic Reconfigurable Intelligent Surfaces
Type
ArticleKAUST Department
Electrical Engineering ProgramComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Physical Science and Engineering (PSE) Division
Date
2021Preprint Posting Date
2020-09-23Permanent link to this record
http://hdl.handle.net/10754/665440
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Show full item recordAbstract
We propose a holographic version of a reconfigurable intelligent surface (RIS) and investigate its application to terahertz (THz) massive multiple-input multiple-output systems. Capitalizing on the miniaturization of THz electronic components, RISs can be implemented by densely packing sub-wavelength unit cells, so as to realize continuous or quasi-continuous apertures and to enable holographic communications. In this paper, in particular, we derive the beam pattern of a holographic RIS. Our analysis reveals that the beam pattern of an ideal holographic RIS can be well approximated by that of an ultra-dense RIS, which has a more practical hardware architecture. In addition, we propose a closed-loop channel estimation (CE) scheme to effectively estimate the broadband channels that characterize THz massive MIMO systems aided by holographic RISs. The proposed CE scheme includes a downlink coarse CE stage and an uplink finer-grained CE stage. The uplink pilot signals are judiciously designed for obtaining good CE performance. Moreover, to reduce the pilot overhead, we introduce a compressive sensing-based CE algorithm, which exploits the dual sparsity of THz MIMO channels in both the angular domain and delay domain. Simulation results demonstrate the superiority of holographic RISs over the non-holographic ones, and the effectiveness of the proposed CE scheme.Citation
Wan, Z., Gao, Z., Gao, F., Di Renzo, M., & Alouini, M.-S. (2021). Terahertz Massive MIMO with Holographic Reconfigurable Intelligent Surfaces. IEEE Transactions on Communications, 1–1. doi:10.1109/tcomm.2021.3064949Sponsors
The work of Z. Gao was supported by the Beijing Municipal Natural Science Foundation under Grant L182024, National Natural Science Foundation of China under Grant 62071044, the Young Elite Scientists Sponsorship Program by CAST under no. YESS20180270, and in part by the Talent Innovation Project of BIT. The work of M. Di Renzo was supported in part by the European Commission through the H2020 ARIADNE project under grant agreement no. 871464 and through the H2020 RISE-6G project under grant agreement no. 101017011. The codes and some other materials about this work may be available at https://gaozhen16.github.ioPublisher
IEEEarXiv
2009.10963Additional Links
https://ieeexplore.ieee.org/document/9374451/https://ieeexplore.ieee.org/document/9374451/
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9374451
http://arxiv.org/pdf/2009.10963
ae974a485f413a2113503eed53cd6c53
10.1109/TCOMM.2021.3064949