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Title: Nonlinear equalization of Hammerstein OFDM systems
Authors: Hong, Xia
Chen, Sheng
Gong, Yu
Harris, Chris J.
Keywords: B-spline neural networks
De Boor algorithm
Equalization
Hammerstein channel
Nonlinear high power amplifier
Orthogonal frequency-division multiplexing
Issue Date: 2014
Publisher: © IEEE
Citation: HONG, X. ... et al, 2014. Nonlinear equalization of Hammerstein OFDM systems. IEEE Transactions on Signal Processing, 62 (21), pp. 5629-5639.
Abstract: A practical orthogonal frequency-division multiplexing (OFDM) system can generally be modelled by the Hammerstein system that includes the nonlinear distortion effects of the high power amplifier (HPA) at transmitter. In this contribution, we advocate a novel nonlinear equalization scheme for OFDM Hammerstein systems. We model the nonlinear HPA, which represents the static nonlinearity of the OFDM Hammerstein channel, by a B-spline neural network, and we develop a highly effective alternating least squares algorithm for estimating the parameters of the OFDM Hammerstein channel, including channel impulse response coefficients and the parameters of the B-spline model. Moreover, we also use another B-spline neural network to model the inversion of the HPA's nonlinearity, and the parameters of this inverting B-spline model can easily be estimated using the standard least squares algorithm based on the pseudo training data obtained as a byproduct of the Hammerstein channel identification. Equalization of the OFDM Hammerstein channel can then be accomplished by the usual one-tap linear equalization as well as the inverse B-spline neural network model obtained. The effectiveness of our nonlinear equalization scheme for OFDM Hammerstein channels is demonstrated by simulation results.
Description: © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Version: Accepted for publication
DOI: 10.1109/TSP.2014.2355773
URI: https://dspace.lboro.ac.uk/2134/25653
Publisher Link: http://dx.doi.org/10.1109/TSP.2014.2355773
ISSN: 1053-587X
Appears in Collections:Published Articles (Mechanical, Electrical and Manufacturing Engineering)

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