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Genetic-Algorithm-Assisted Maximum-Likelihood Detection of OFDM Symbols in the Presence of Nonlinear Distortions | IEEE Journals & Magazine | IEEE Xplore

Genetic-Algorithm-Assisted Maximum-Likelihood Detection of OFDM Symbols in the Presence of Nonlinear Distortions


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 estimat...Show More

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
Published in: IEEE Transactions on Communications ( Volume: 55, Issue: 5, May 2007)
Page(s): 854 - 859
Date of Publication: 15 May 2007

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I. Introduction

Multicarrier modulations (MCMs) [1] are regarded as emerging technologies for new-generation networking applications. In particular, orthogonal frequency-division multiplexing (OFDM) can profit by full-digital fast Fourier transform (FFT)-based implementation and is intrinsically resilient against frequency-selective channel distortions [1]. At present, two open problems limit the efficiency of OFDM techniques when employed in real-world application testbeds: nonlinear distortions involved by power amplifiers [2] and channel-estimation errors occurring in time-varying multipath fading channels [3]. In this letter, we are focusing on the problem of the optimum OFDM symbol recovery in the presence of nonlinear distortions.

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