Roger Varea, S.; Gonzalez, A.; Almenar Terre, V.; Vidal Maciá, AM. (2011). Practical aspects of preprocessing techniques for K-Best tree search MIMO detectors. Computers and Electrical Engineering. 37(4):451-460. doi:10.1016/j.compeleceng.2011.05.007
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/46832
Title:
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Practical aspects of preprocessing techniques for K-Best tree search MIMO detectors
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Author:
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Roger Varea, Sandra
Gonzalez, Alberto
Almenar Terré, Vicenç
Vidal Maciá, Antonio Manuel
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UPV Unit:
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Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia
Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
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Issued date:
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Abstract:
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It has been shown in several works that some preprocessing techniques can improve data detection performance when they are applied to the channel matrix of MIMO wireless systems. In particular, these techniques can be used ...[+]
It has been shown in several works that some preprocessing techniques can improve data detection performance when they are applied to the channel matrix of MIMO wireless systems. In particular, these techniques can be used previously to K-Best tree search algorithms, and they are known to achieve successful results. Throughout this work, the performance and complexity of two preprocessing techniques (VBLAST ZF-DFE ordering and LLL lattice-reduction) are evaluated and compared. The LLL algorithm and a recently proposed fixed-complexity version of it are tested. In addition, a low-complexity implementation of the VBLAST ZF-DFE method is proposed. Results show that the LLL preprocessing is less costly than the VBLAST ZF-DFE ordering in average. Also, the BER curves of the K-Best detector in a 4 x 4 MIMO system reveal that the LLL method can only present better detection performance than the VBLAST ZF-DFE ordering for high SNRs and low values of K. (C) 2011 Elsevier Ltd. All rights reserved.
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Subjects:
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Channel matrices
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Data detection
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Detection performance
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Lattice-reduction
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LLL algorithm
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Low-complexity
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MIMO detectors
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Preprocessing techniques
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Tree search
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Tree search algorithm
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V-BLAST
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Wireless systems
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Copyrigths:
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Cerrado |
Source:
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Computers and Electrical Engineering. (issn:
0045-7906
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DOI:
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10.1016/j.compeleceng.2011.05.007
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Publisher:
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Elsevier
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Publisher version:
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http://dx.doi.org/10.1016/j.compeleceng.2011.05.007
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Project ID:
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info:eu-repo/grantAgreement/MICINN//TEC2009-13741/ES/Spatial Audio Systems Based On Massive Parallel Processing Of Multichannel Acoustic Signals With General Purpose-Graphics Processing Units (Gp-Gpu) And Multicores/ /
info:eu-repo/grantAgreement/Generalitat Valenciana//PROMETEO09%2F2009%2F013/ES/Computacion de altas prestaciones sobre arquitecturas actuales en porblemas de procesado múltiple de señal/
info:eu-repo/grantAgreement/MEC//AP2007-01417/ES/AP2007-01417/
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Thanks:
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This work was supported by the PROMETEO/2009/013 and TEC2009-13741 projects and by AP2007-01417 FPU grant from the Spanish Ministry of Education.
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Type:
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Artículo
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