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dc.contributor.authorWan, Ziwei
dc.contributor.authorGao, Zhen
dc.contributor.authorAlouini, Mohamed-Slim
dc.date.accessioned2020-07-29T13:13:23Z
dc.date.available2020-07-29T13:13:23Z
dc.date.issued2020
dc.identifier.citationWan, Z., Gao, Z., & Alouini, M.-S. (2020). Broadband Channel Estimation for Intelligent Reflecting Surface Aided mmWave Massive MIMO Systems. ICC 2020 - 2020 IEEE International Conference on Communications (ICC). doi:10.1109/icc40277.2020.9149146
dc.identifier.isbn978-1-7281-5090-1
dc.identifier.issn1550-3607
dc.identifier.doi10.1109/ICC40277.2020.9149146
dc.identifier.urihttp://hdl.handle.net/10754/664500
dc.description.abstractThis paper investigates the broadband channel estimation (CE) for intelligent reflecting surface (IRS)-aided millimeter-wave (mmWave) massive MIMO systems. The CE for such systems is a challenging task due to the large dimension of both the active massive MIMO at the base station (BS) and passive IRS. To address this problem, this paper proposes a compressive sensing (CS)-based CE solution for IRS-aided mmWave massive MIMO systems, whereby the angular channel sparsity of large-scale array at mmWave is exploited for improved CE with reduced pilot overhead. Specifically, we first propose a downlink pilot transmission framework. By designing the pilot signals based on the prior knowledge that the line-of-sight dominated BS-to-IRS channel is known, the high-dimensional channels for BS-to-user and IRS-to-user can be jointly estimated based on CS theory. Moreover, to efficiently estimate broadband channels, a distributed orthogonal matching pursuit algorithm is exploited, where the common sparsity shared by the channels at different subcarriers is utilized. Additionally, the redundant dictionary to combat the power leakage is also designed for the enhanced CE performance. Simulation results demonstrate the effectiveness of the proposed scheme.
dc.publisherIEEE
dc.relation.urlhttps://ieeexplore.ieee.org/document/9149146/
dc.relation.urlhttps://ieeexplore.ieee.org/document/9149146/
dc.relation.urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9149146
dc.relation.urlhttp://arxiv.org/pdf/2002.01629
dc.rightsArchived with thanks to IEEE
dc.rightsThis file is an open access version redistributed from: http://arxiv.org/pdf/2002.01629
dc.subjectMillimeter-wave (mmWave)
dc.subjectintelligent reflecting surface (IRS)
dc.subjectmassive MIMO
dc.subjectcompressive sensing (CS).
dc.titleBroadband Channel Estimation for Intelligent Reflecting Surface Aided mmWave Massive MIMO Systems
dc.typeConference Paper
dc.contributor.departmentCommunication Theory Lab
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.conference.date7-11 June 2020
dc.conference.nameICC 2020 - 2020 IEEE International Conference on Communications (ICC)
dc.conference.locationDublin, Ireland
dc.eprint.versionPre-print
dc.contributor.institutionBeijing Institute of Technology,School of Information and Electronics,Beijing,P. R. China,100081
dc.identifier.arxividarXiv:2002.01629
kaust.personAlouini, Mohamed-Slim
refterms.dateFOA2020-12-07T12:10:30Z
dc.date.published-online2020-07-27
dc.date.published-print2020-06


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