Florent Kadrija (8 results)
Language: English
Published by VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2013
- Softcover
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Condition: New. pp. 80.
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Taschenbuch. Condition: Neu. Iterative Channel Estimation for UMTS Long Term Evolution | Comparison of Algorithms for A-Posteriori, Extrinsic and Hard Feedback Information | Florent Kadrija | Taschenbuch | 80 S. | Englisch | 2015 | AV Akademikerverlag | EAN 9783639470345 | Verantwortliche Person für die EU: preigu GmbH & Co. KG,… Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
- Softcover
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Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book, different iterative channel estimation algorithms for Long term Evolution (LTE) downlink are investigated. LTE uses coherent detection, which requires channel state information. In order to achieve high data rate trans…mission over mobile radio channels, it is essential to have accurate channel state information at the receiver side. For channel estimation purpose LTE provides training data known as pilot symbols. The matter of discussion is whether the accuracy of channel estimate based on pilot symbols is satisfactorily sufficient to achieve high data rate transmission. Channel estimate can be further enhanced, if after pilot based channel estimation, additional information such as the hard or soft estimated data symbols from the decoder is utilized by the channel estimator. Using this additional information, different channel estimation algorithms like Least Square (LS), Linear Minimum Mean Square Error (LMMSE) and Approximated LMMSE (ALMMSE) are derived. Their performance is discussed and compared with each other. The impact of processing either extrinsic, a-posteriori or hard feedback information in the channel estimator is investigated. To assess the performance, the channel estimators are compared in terms of Mean Square Error (MSE) and throughput over SNR for Single Input Single Output (SISO) and Multiple Input Multiple Output (MIMO) antenna setups. 80 pp. Englisch.
Language: English
Published by VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2013
- Softcover
- Print on Demand
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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Condition: New. Print on Demand pp. 80 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.
Language: English
Published by VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2013
- Softcover
- Print on Demand
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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Condition: New. PRINT ON DEMAND pp. 80.
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Seller: moluna, Greven, Germanymoluna
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kadrija FlorentFlorent Kadrija has earned a bachelor s degree in Electrical and Computer Engineering at the University of Prishtina and a master s degree in Telecommunications at the Vienna University o…f Technology. Currently, he is .
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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book, different iterative channel estimation algorithms for Long term Evolution (LTE) downlink are investigated. LTE uses coherent detection, which requires channel state information. In order to achieve high data rate transmissi…on over mobile radio channels, it is essential to have accurate channel state information at the receiver side. For channel estimation purpose LTE provides training data known as pilot symbols. The matter of discussion is whether the accuracy of channel estimate based on pilot symbols is satisfactorily sufficient to achieve high data rate transmission. Channel estimate can be further enhanced, if after pilot based channel estimation, additional information such as the hard or soft estimated data symbols from the decoder is utilized by the channel estimator. Using this additional information, different channel estimation algorithms like Least Square (LS), Linear Minimum Mean Square Error (LMMSE) and Approximated LMMSE (ALMMSE) are derived. Their performance is discussed and compared with each other. The impact of processing either extrinsic, a-posteriori or hard feedback information in the channel estimator is investigated. To assess the performance, the channel estimators are compared in terms of Mean Square Error (MSE) and throughput over SNR for Single Input Single Output (SISO) and Multiple Input Multiple Output (MIMO) antenna setups.
