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Improved Maximum Likelihood Detection through Sphere Decoding combined with Box Optimization

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Improved Maximum Likelihood Detection through Sphere Decoding combined with Box Optimization

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García Mollá, VM.; Vidal Maciá, AM.; González Salvador, A.; Roger Varea, S. (2014). Improved Maximum Likelihood Detection through Sphere Decoding combined with Box Optimization. Signal Processing. 98:284-294. doi:10.1016/j.sigpro.2013.11.041

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/49446

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Title: Improved Maximum Likelihood Detection through Sphere Decoding combined with Box Optimization
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia
Issued date:
Abstract:
Sphere Decoding is a popular Maximum Likelihood algorithm that can be used to detect signals coming from multiple-input, multiple-output digital communication systems. It is well known that the complexity required to ...[+]
Subjects: MIMO communication systems , Sphere decoding , Box minimization
Copyrigths: Reserva de todos los derechos
Source:
Signal Processing. (issn: 0165-1684 )
DOI: 10.1016/j.sigpro.2013.11.041
Publisher:
Elsevier
Publisher version: http://dx.doi.org/10.1016/j.sigpro.2013.11.041
Description: this is the author’s version of a work that was accepted for publication in Signal Processing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Signal Processing, [VOL 98, may 14] DOI 10.1016/j.sigpro.2013.11.041
Thanks:
This work has been partially funded by Universitat Politecnica de Valencia through Programa de Apoyo a la Investigacion y Desarrollo de la UPV (PAID-06-11) and (PAID-05-12), by Generalitat Valenciana through projects ...[+]
Type: Artículo

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