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Please use this identifier to cite or link to this item:
http://hdl.handle.net/10016/14425
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| Title: | Reduction of power envelope fluctuations in OFDM signals by using neural networks |
| Author(s): | Jabrane, Younes
Gil-Jiménez, Víctor P.
García-Armada, Ana
Ait Es Said, Brahim
Ait Ouahman, Abdellah |
| Publisher: | IEEE |
| Issued date: | Jul-2010 |
| Citation: | IEEE Communications Letters, (July 2010), 14(7), 599-601 |
| URI: | http://hdl.handle.net/10016/14425 |
| ISSN: | 1089-7798 |
| DOI: | http://dx.doi.org/10.1109/LCOMM.2010.07.100385 |
| Abstract: | One of the main drawbacks of Orthogonal Frequency Division Multiplexing (OFDM) are the large fluctuations of its power envelope. In this letter, a novel and efficient scheme based on Multilayer Perceptron (MLP) Neural Networks (NN) is proposed. The NN synthesizes the Active Constellation Expansion - (ACE) technique which is able to drastically reduce envelope fluctuations. This is achieved with much lower complexity, faster convergence, and better performance compared to previously available methods. |
| Sponsor: | This work has been partly funded by the projects MULTI-ADAPTIVE (TEC2008-06327-C03-02), COMONSENS (CSD2008-00010), and the AECI Program of Research Cooperation with Morocco. |
| Publisher version: | http://dx.doi.org/10.1109/LCOMM.2010.07.100385 |
| Keywords: | OFDM
PAPR
Cubic metric
Neural networks |
| Rights: | © 2010 IEEE |
| Appears in Collections: | DTSC - GC - Artículos de Revistas
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