Title :
Genetic-Algorithm-Assisted Maximum-Likelihood Detection of OFDM Symbols in the Presence of Nonlinear Distortions
Author :
Sacchi, Claudio ; Donelli, Massimo ; De Natale, Francesco G B
Author_Institution :
Dept. of Inf. & Commun. Technol., Trento Univ.
fDate :
5/1/2007 12:00:00 AM
Abstract :
This letter aims at proposing the use of evolutionary computation methodologies (i.e., genetic algorithms) in order to solve the problem of the maximum-likelihood estimation of orthogonal frequency-division multiplexing symbols in the presence of nonlinear distortions. Experimental results can prove the effectiveness of the proposed detection algorithm achieved with a reasonable computational load
Keywords :
OFDM modulation; genetic algorithms; maximum likelihood detection; nonlinear distortion; OFDM; detection algorithm; genetic algorithm; maximum-likelihood detection; maximum-likelihood estimation; nonlinear distortions; orthogonal frequency-division multiplexing; Fading; Frequency division multiplexing; Genetic algorithms; Maximum likelihood detection; Maximum likelihood estimation; Nonlinear distortion; OFDM modulation; Power amplifiers; Radio frequency; Radiofrequency amplifiers; Genetic algorithms (GAs); maximum-likelihood (ML) detection; multicarrier modulation (MCM); nonlinear distortion; orthogonal frequency-division multiplexing (OFDM);
Journal_Title :
Communications, IEEE Transactions on
DOI :
10.1109/TCOMM.2007.896126
