Title :
Reduction of Power Envelope Fluctuations in OFDM Signals by using Neural Networks
Author :
Jabrane, Younes ; Jiménez, Víctor P Gil ; Armada, Ana García ; Said, Brahim Ait Es ; Ouahman, Abdellah Ait
fDate :
7/1/2010 12:00:00 AM
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.
Keywords :
OFDM modulation; multilayer perceptrons; telecommunication computing; OFDM signals; active constellation expansion; multilayer perceptron; neural networks; orthogonal frequency division multiplexing; power envelope fluctuation reduction; Artificial neural networks; Complexity theory; Convergence; Fluctuations; Gas insulated transmission lines; Multi-layer neural network; Multilayer perceptrons; Neural networks; Neurons; OFDM; Peak to average power ratio; Time domain analysis; Training; OFDM; PAPR; cubic metric; neural networks;
Journal_Title :
Communications Letters, IEEE
DOI :
10.1109/LCOMM.2010.07.100385