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dc.contributor.authorWan, Ziwei
dc.contributor.authorGao, Zhen
dc.contributor.authorGao, Feifei
dc.contributor.authorRenzo, Marco Di
dc.contributor.authorAlouini, Mohamed-Slim
dc.date.accessioned2021-03-11T05:42:49Z
dc.date.available2020-10-05T10:35:07Z
dc.date.available2021-03-11T05:42:49Z
dc.date.issued2021
dc.identifier.citationWan, 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.2021.3064949
dc.identifier.issn1558-0857
dc.identifier.doi10.1109/TCOMM.2021.3064949
dc.identifier.urihttp://hdl.handle.net/10754/665440
dc.description.abstractWe 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.
dc.description.sponsorshipThe 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.io
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttps://ieeexplore.ieee.org/document/9374451/
dc.relation.urlhttps://ieeexplore.ieee.org/document/9374451/
dc.relation.urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9374451
dc.rightsArchived with thanks to IEEE Transactions on Communications
dc.subjectTerahertz communications
dc.subjectreconfigurable intelligent surface
dc.subjectmassive MIMO
dc.subjectholographic communications
dc.subjectcompressive sensing (CS)
dc.subjectchannel estimation
dc.titleTerahertz Massive MIMO with Holographic Reconfigurable Intelligent Surfaces
dc.typeArticle
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.identifier.journalIEEE Transactions on Communications
dc.eprint.versionPost-print
dc.contributor.institutionSchool of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China, and Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology, Beijing 100081, China.
dc.contributor.institutionInstitute for Artificial Intelligence, Tsinghua University (THUAI), Beijing 100084, China and State Key Laboratory of Intelligent Technologies and Systems, Tsinghua University, Beijing 100084, China, and Beijing National Research Center for Information Science and Technology (BNRist), Department of Automation, Tsinghua University, Beijing 100084, China.
dc.contributor.institutionUniversité Paris-Saclay, CNRS, Centrale Supélec, Laboratoire des Signaux et Systèmes, 3 Rue Joliot-Curie, 91192 Gif-sur-Yvette, France.
dc.identifier.arxivid2009.10963
kaust.personAlouini, Mohamed-Slim
refterms.dateFOA2020-10-05T10:35:37Z


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