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Nonlinear equalization of Hammerstein OFDM systems

Hong, X., Chen, S., Gong, Y. and Harris, C. J. (2014) Nonlinear equalization of Hammerstein OFDM systems. IEEE Transactions on Signal Processing, 62 (21). pp. 5629-5639. ISSN 1053-587X

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To link to this item DOI: 10.1109/TSP.2014.2355773

Abstract/Summary

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.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:39723
Uncontrolled Keywords:B-spline neural networks, De Boor algorithm, equalization, Hammerstein channel, nonlinear high power amplifier, orthogonal frequency-division multiplexing.
Publisher:IEEE

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