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dc.contributor.authorSokal, Bruno-
dc.contributor.authorAlmeida, André Lima Férrer de-
dc.contributor.authorHaardt, Martin Haardt-
dc.date.accessioned2021-08-18T18:26:57Z-
dc.date.available2021-08-18T18:26:57Z-
dc.date.issued2017-
dc.identifier.citationSOKAL, Bruno; ALMEIDA, André Lima Férrer de; HAARDT, Martin. Rank-one tensor modeling approach to joint channel and symbol estimation in two-hop MIMO relaying systems. In: SIMPÓSIO BRASILEIRO DE TELECOMUNICAÇÕES E PROCESSAMENTO DE SINAIS – SbrT, XXXV., 3 a 6 set. 2017. São Pedro-SP. Anais[…], São Pedro-SP, 2017.p.37-41.pt_BR
dc.identifier.urihttp://www.repositorio.ufc.br/handle/riufc/60023-
dc.description.abstractThis paper proposes two semi-blind receives for joint channel and symbol estimation in MIMO relay-based communication systems. These receivers are developed for a two-hop system, assuming a tensor coding at the source and relay nodes. The central idea of the proposed approach is on the rank-one tensor modeling of the received signal, which allows the use of efficient estimation algorithms. The first receiver utilizes an iterative solution based on the alternating least squares (ALS) algorithm, while the second provides closed-form estimations of the channel and symbol matrices from a truncated higher order singular value decomposition (T-HOSVD). The proposed approach has a lower complexity compared to the receiver developed in a previous work, while providing remarkable performance.pt_BR
dc.language.isopt_BRpt_BR
dc.publisherhttps://www.sbrt.org.br/sbrt2017pt_BR
dc.subjectMIMO systemspt_BR
dc.subjectCooperative communicationspt_BR
dc.subjectTensor decompositionspt_BR
dc.subjectSemi-blind receiverpt_BR
dc.titleRank-One Tensor Modeling Approach to Joint Channel and Symbol Estimation in Two-Hop MIMO Relaying Systemspt_BR
dc.typeArtigo de Eventopt_BR
dc.description.abstract-ptbrThis paper proposes two semi-blind receives for joint channel and symbol estimation in MIMO relay-based communication systems. These receivers are developed for a two-hop system, assuming a tensor coding at the source and relay nodes. The central idea of the proposed approach is on the rank-one tensor modeling of the received signal, which allows the use of efficient estimation algorithms. The first receiver utilizes an iterative solution based on the alternating least squares (ALS) algorithm, while the second provides closed-form estimations of the channel and symbol matrices from a truncated higher order singular value decomposition (T-HOSVD). The proposed approach has a lower complexity compared to the receiver developed in a previous work, while providing remarkable performance.pt_BR
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