Institutional Repository
Technical University of Crete
Technical University of Crete
EN
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EL
| URI | http://purl.tuc.gr/dl/dias/BA2AB2CA-1120-4B65-B325-30F5077C935F | - |
| Identifier | https://doi.org/10.26233/heallink.tuc.91437 | - |
| Language | en | - |
| Extent | 79 pages | en |
| Extent | 3.4 megabytes | en |
| Title | Estimation of sparse channels in 5G wireless systems | en |
| Title | Εκτίμηση αραιών καναλιών σε ασύρματα συστήματα 5ης γενιάς | el |
| Creator | Paktitis Spyridon | en |
| Creator | Πακτιτης Σπυριδων | el |
| Contributor [Thesis Supervisor] | Liavas Athanasios | en |
| Contributor [Thesis Supervisor] | Λιαβας Αθανασιος | el |
| Contributor [Committee Member] | Karystinos Georgios | en |
| Contributor [Committee Member] | Καρυστινος Γεωργιος | el |
| Contributor [Committee Member] | Μπερμπερίδης, Κώστας | en |
| Publisher | Πολυτεχνείο Κρήτης | el |
| Publisher | Technical University of Crete | en |
| Academic Unit | Technical University of Crete::School of Electrical and Computer Engineering | en |
| Academic Unit | Πολυτεχνείο Κρήτης::Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών | el |
| Content Summary | In this Diploma Thesis, we study a novel Channel State Information on the Transmitter side (CSIT) algorithm for the estimation of the CSIT in a multiuser, Frequency Division Multiplexing (FDD), massive MIMO wireless system. The main characteristic of a massive MIMO system is the large number of antennas at the Base Station (BS). This fact puts significant difficulties at the channel estimation process but offers significant benefits regarding spectral and energy efficiency, reliability, and capacity. First, we present the concept of Compressive Sensing and the important research results of J.A. Tropp and A.C. Gilbert, including an algorithm for sparse signal recovery from random measurements via Orthogonal Matching Pursuit. In their work, Tropp and Gilbert propose a remarkably simple algorithm for tackling signal estimation when dealing with sparse channel matrices. Then, we familiarise ourselves with the Angular Domain representation of signals, mainly based on the book by D. Tse and P. Viswanath. Last, we present an algorithm for efficient channel estimation in Massive MIMO FDD systems proposed in a paper by X. Rao and V. K. N. Lau. We also studied the work of J. C. Shen, J. Zhang, K. C. Chen and K. B. Lataief (see also the work of M. Massod, L.H. Afify and T.Y. Al-Naffouri). We apply and test the algorithm in various scenarios of interest, revealing that efficient massive MIMO channel estimation is possible under the hypothesis of sparsity in the angular domain. | en |
| Type of Item | Διπλωματική Εργασία | el |
| Type of Item | Diploma Work | en |
| License | http://creativecommons.org/licenses/by-nc/4.0/ | en |
| Date of Item | 2022-02-09 | - |
| Date of Publication | 2022 | - |
| Subject | Sparse channel estimation | en |
| Subject | Orthogonal Matching Pursuit (OMP) | en |
| Subject | Angular Domain representation of signals | en |
| Subject | Massive MIMO | en |
| Bibliographic Citation | Spyridon Paktitis, "Estimation of Sparse Channels in 5G Wireless Systems", Diploma Work, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2022 | en |
| Bibliographic Citation | Σπυρίδων Πακτίτης, "Εκτίμηση αραιών καναλιών σε ασύρματα συστήματα 5ης γενιάς", Διπλωματική Εργασία, Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών, Πολυτεχνείο Κρήτης, Χανιά, Ελλάς, 2022 | el |
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